# COMPSCI/MATH 514: Numerical Analysis | UW–Madison [View on UW Courses](https://uwcourses.com/courses/COMPSCI_MATH_514) ## Dataset ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ### repository twangodev/uwcourses ### schema version 6 ### importer version 7 ### projection id 52a78527ff09011d88cb04c7d43867d9fbfec2930bf1dd2ec359ebd2844e0b07 ### observed at 2026-09-07T15:55:43.033547+00:00 ### built at 2026-09-10T19:50:42.743001+00:00 ### courses 8951 ### current instructors 5754 ### limited false ### terms * 1272 * 1264 * 1262 * 1254 * 1252 * 1244 * 1242 * 1234 * 1232 * 1224 * 1222 * 1212 * 1204 * 1202 * 1194 * 1192 * 1184 * 1182 * 1174 * 1172 * 1164 * 1162 * 1154 * 1152 * 1144 * 1142 * 1134 * 1132 * 1124 * 1122 * 1114 * 1112 * 1104 * 1102 * 1094 * 1092 * 1084 * 1082 * 1074 * 1072 ### term 1272 ### departments | subject | count | | --------- | ----- | | AAE | 90 | | ABT | 20 | | ACCTIS | 36 | | ACTSCI | 14 | | AFAERO | 10 | | AFRICAN | 87 | | AFROAMER | 71 | | AGROECOL | 21 | | AMERIND | 53 | | ANAT\&PHY | 7 | | ANATOMY | 2 | | ANESTHES | 8 | | ANSCI | 57 | | ANTHRO | 95 | | ART | 125 | | ARTED | 10 | | ARTHIST | 121 | | ASIALANG | 129 | | ASIAN | 109 | | ASIANAM | 28 | | ASTRON | 38 | | ATMOCN | 69 | | BIOCHEM | 51 | | BIOCORE | 10 | | BIOLOGY | 14 | | BIOMDSCI | 18 | | BME | 66 | | BMI | 41 | | BMOLCHEM | 10 | | BOTANY | 69 | | BSE | 44 | | C\&ESOC | 73 | | CBE | 48 | | CHEM | 101 | | CHICLA | 52 | | CIVENGR | 133 | | CLASSICS | 47 | | CNP | 10 | | CNSRSCI | 50 | | COMARTS | 137 | | COMPBIO | 15 | | COMPLIT | 11 | | COMPSCI | 138 | | COUNPSY | 78 | | CRB | 19 | | CS\&D | 71 | | CSCS | 40 | | CURRIC | 193 | | DANCE | 93 | | DERM | 8 | | DS | 88 | | DYSCI | 35 | | ECE | 155 | | ECON | 145 | | EDPOL | 114 | | EDPSYCH | 97 | | ELPA | 70 | | EMA | 53 | | EMERMED | 17 | | ENGL | 206 | | ENTOM | 40 | | ENVIRST | 148 | | EP | 15 | | EPD | 67 | | ESL | 16 | | F\&WECOL | 60 | | FAMMED | 22 | | FINANCE | 50 | | FOLKLORE | 40 | | FOODSCI | 43 | | FRENCH | 63 | | GEN\&WS | 145 | | GENBUS | 72 | | GENECSLR | 17 | | GENETICS | 60 | | GEOG | 113 | | GEOSCI | 83 | | GERMAN | 82 | | GLE | 48 | | GNS | 38 | | GREEK | 27 | | HDFS | 41 | | HEBR-BIB | 13 | | HEBR-MOD | 10 | | HISTORY | 233 | | HISTSCI | 56 | | HONCOL | 13 | | ILS | 43 | | INFOSYS | 9 | | INTEGART | 7 | | INTEGSCI | 22 | | INTER-AG | 18 | | INTER-HE | 11 | | INTER-LS | 22 | | INTEREGR | 16 | | INTLBUS | 21 | | INTLST | 50 | | ISYE | 83 | | ITALIAN | 53 | | JEWISH | 56 | | JOURN | 88 | | KINES | 128 | | LACIS | 26 | | LANDARC | 61 | | LATIN | 24 | | LAW | 120 | | LEGALST | 48 | | LINGUIS | 35 | | LIS | 89 | | LITTRANS | 78 | | LSC | 52 | | M\&ENVTOX | 7 | | MARKETNG | 62 | | MATH | 153 | | MDGENET | 8 | | ME | 130 | | MEDHIST | 43 | | MEDICINE | 60 | | MEDIEVAL | 32 | | MEDPHYS | 39 | | MEDSC-M | 29 | | MEDSC-V | 41 | | MHR | 68 | | MICROBIO | 45 | | MILSCI | 16 | | MM\&I | 22 | | MOLBIOL | 6 | | MS\&E | 59 | | MUSIC | 165 | | MUSPERF | 126 | | NAVSCI | 20 | | NE | 44 | | NEURODPT | 11 | | NEUROL | 7 | | NEURSURG | 4 | | NTP | 11 | | NURSING | 111 | | NUTRSCI | 65 | | OBS\&GYN | 18 | | OCCTHER | 39 | | ONCOLOGY | 14 | | OPHTHALM | 5 | | OTM | 43 | | PATH | 34 | | PATH-BIO | 29 | | PEDIAT | 26 | | PHARMACY | 31 | | PHILOS | 77 | | PHMCOL-M | 11 | | PHMPRAC | 45 | | PHMSCI | 60 | | PHYASST | 37 | | PHYSICS | 88 | | PHYSIOL | 3 | | PHYTHER | 37 | | PLANTSCI | 52 | | PLPATH | 35 | | POLISCI | 192 | | POPHLTH | 58 | | PORTUG | 33 | | PSYCH | 101 | | PSYCHIAT | 22 | | PUBAFFR | 54 | | PUBLHLTH | 23 | | RADIOL | 11 | | REALEST | 41 | | RELIGST | 90 | | RHABMED | 9 | | RMI | 24 | | RP\&SE | 102 | | S\&APHM | 17 | | SCANDST | 73 | | SLAVIC | 89 | | SOC | 149 | | SOCWORK | 87 | | SOILSCI | 46 | | SPANISH | 83 | | SRMED | 21 | | STAT | 94 | | STDYABRD | 52 | | STS | 8 | | SURGERY | 25 | | SURGSCI | 33 | | THEATRE | 91 | | URBRPL | 60 | | UROLOGY | 5 | | ZOOLOGY | 89 | ## course ### run id 20260907T155543-ce3781c4 ### semester 1272 ### observed at 2026-09-07 15:55:43.033547+00:00 ### record version id c84dd1fee494acf75dab3c2092ffc8fc5bc0cb4784b7788f7567bd48a44588ff ### course id COMPSCI/MATH 514 ### course uid course\_f237678d9fac59631b4aa4ff ### catalog version id b24c8bb98ac4b841d578b988699fd857d6d565e261628d677303377c2b1efdc2 ### course number 514 ### subjects * COMPSCI * MATH ### title NUMERICAL ANALYSIS ### description Polynomial forms, divided differences. Polynomial interpolation. Polynomial approximation: uniform approximation and Chebyshev polynomials, least-squares approximation and orthogonal polynomials. Numerical differentiation and integration. Splines, B-splines and spline approximation. Numerical methods for solving initial and boundary value problems for ordinary differential equations. ### requirements text (MATH 320,340,341,345, or375), (MATH 322,341,375,421, or521), and (COMP SCI 200,220,300, or placement intoCOMP SCI 300), graduate/professional standing, or declared in Mathematics VISP (undergraduate or graduate) ### credits min 3 ### credits max 3 ### credit offering ids * 1272:266:004270 * 1272:600:004270 ### llm job id enrich-f516c4d3e82cfe326b4f5f54 ### llm output id d0cc749cdefdb62694a6cbff00b3f89b9ffc869c0781a3b9474e9d5bc28d80fb ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Numerical Analysis covers polynomial approximation, interpolation, splines, numerical integration, and methods for solving ordinary differential equations. ### llm topics * Polynomial interpolation * Polynomial approximation * Numerical differentiation and integration * Spline approximation * Numerical methods for ODEs ### llm skills * Polynomial interpolation and approximation using Chebyshev and orthogonal polynomials. * Numerical differentiation and integration techniques. * Spline and B-spline approximation methods. * Solving initial and boundary value problems for ordinary differential equations. ### llm assumed background * Prerequisite knowledge in linear algebra, differential equations, and programming fundamentals. ### llm search phrases * numerical analysis polynomial interpolation * numerical methods differential equations * spline approximation Chebyshev * COMPSCI MATH 514 prerequisites ### llm requirements status needs\_review ### llm student summary status valid ### llm experience status valid ### catalog variants None recorded. ### student summary #### context hash 31389f08e399a8aaae0b2a8e33dc269a04e61b63803f1a9aa87c55e34cc0a93e #### course id COMPSCI/MATH 514 #### current instructors ```json [ { "instructor_uid": "instructor_ab5c68c5e0b538ecb5a4949f", "message": null, "name": "Qin Li", "review_status": "supported", "rmp_instructor_id": "rmp:2059558", "summary": [ { "citations": [ { "instructor_name": "Qin Li", "review_date": "2015-12-22 13:26:02 +0000 UTC", "review_id": "dc4bd03251aa3769c2e7e3d1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI1ODAyMDYz", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2017-01-18 16:08:45 +0000 UTC", "review_id": "b548c2047381f6f62e056453", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI3NzQ5Nzg5", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2018-12-31 01:15:28 +0000 UTC", "review_id": "74adc4040ee9f474c8ad9b38", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMxMTc4MzI0", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2019-01-29 16:43:17 +0000 UTC", "review_id": "d02b5f419b12026501d4f11f", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMxMzE2MzQy", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2020-05-03 21:15:27 +0000 UTC", "review_id": "f3192ba4974064931f744dbf", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMzMTkwNzE0", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2024-06-01 02:14:34 +0000 UTC", "review_id": "76c06214e8007d6af932ae74", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTM5NTQwNzQ2", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" } ], "text": "Qin Li receives consistent praise for clear lectures, approachability, and helpful office hours. Reviewers note she explains difficult concepts well and provides exam guidance. While some find the workload light, others describe the class as tough but meaningful, highlighting her kindness and deep knowledge." }, { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1192", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1192", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" } ], "text": "Recent recorded grades — Fall 2018: 2.98 GPA, 45.3% A/AB (n=106 letter grades); Fall 2020: 2.94 GPA, 42.0% A/AB (n=50 letter grades); Spring 2024: 2.89 GPA, 42.6% A/AB (n=47 letter grades)." } ] } ] ``` #### difficulty workload Reviewers describe the workload as manageable with relative homework, but note a large volume of material and a tough class environment requiring strong math preparation. ```json { "citations": [ { "instructor_name": "Qin Li", "review_date": "2017-01-18 16:08:45 +0000 UTC", "review_id": "b548c2047381f6f62e056453", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI3NzQ5Nzg5", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2020-05-03 21:15:27 +0000 UTC", "review_id": "f3192ba4974064931f744dbf", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMzMTkwNzE0", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2024-06-01 02:14:34 +0000 UTC", "review_id": "76c06214e8007d6af932ae74", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTM5NTQwNzQ2", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" } ] } ``` #### errors None recorded. #### historical context Qin Li is the current instructor, but reviews for historical professors like Chenxi Wu describe confusing lectures and exams unrelated to coursework. Chris Rycroft receives polarized feedback, with some praising his enthusiasm and others calling his lectures disorganized. Saverio Spagnolie is noted for engaging lectures and breaking down difficult concepts effectively. ```json { "citations": [ { "instructor_name": "Chenxi Wu", "review_date": "2020-12-14 19:08:53 +0000 UTC", "review_id": "bba838303db351a1104306e5", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2652881", "source_review_id": "UmF0aW5nLTM0MDY4MTU2", "source_url": "https://www.ratemyprofessors.com/professor/2652881", "type": "review" }, { "instructor_name": "Chenxi Wu", "review_date": "2020-12-19 04:25:11 +0000 UTC", "review_id": "0ef7255d3fbf58771d301776", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2652881", "source_review_id": "UmF0aW5nLTM0MTQ1Mzcy", "source_url": "https://www.ratemyprofessors.com/professor/2652881", "type": "review" }, { "instructor_name": "Chenxi Wu", "review_date": "2021-01-03 02:34:19 +0000 UTC", "review_id": "af52d8cd22a4e0b8cb609cff", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2652881", "source_review_id": "UmF0aW5nLTM0MjI3NTQ1", "source_url": "https://www.ratemyprofessors.com/professor/2652881", "type": "review" }, { "instructor_name": "Saverio Spagnolie", "review_date": "2021-11-18 05:48:35 +0000 UTC", "review_id": "d831adea164d2d4d441dbef1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2045894", "source_review_id": "UmF0aW5nLTM1MjY0MTEy", "source_url": "https://www.ratemyprofessors.com/professor/2045894", "type": "review" }, { "instructor_name": "Saverio Spagnolie", "review_date": "2021-12-24 02:06:41 +0000 UTC", "review_id": "4121fe2e12b2dcb96880a035", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2045894", "source_review_id": "UmF0aW5nLTM1NjQ2MzY1", "source_url": "https://www.ratemyprofessors.com/professor/2045894", "type": "review" }, { "instructor_name": "Chris Rycroft", "review_date": "2023-05-17 20:57:10 +0000 UTC", "review_id": "bdbac56f84a062e6b2519725", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2868294", "source_review_id": "UmF0aW5nLTM3OTQ3Njk5", "source_url": "https://www.ratemyprofessors.com/professor/2868294", "type": "review" }, { "instructor_name": "Chris Rycroft", "review_date": "2023-10-29 22:02:24 +0000 UTC", "review_id": "512899ecabc7ec18a2f26ba0", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2868294", "source_review_id": "UmF0aW5nLTM4MzIwMjI3", "source_url": "https://www.ratemyprofessors.com/professor/2868294", "type": "review" }, { "instructor_name": "Laurel Ohm", "review_date": "2024-12-02 20:52:42 +0000 UTC", "review_id": "ebb938216f88dfd5c548f209", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2924874", "source_review_id": "UmF0aW5nLTQwMDY5MTMz", "source_url": "https://www.ratemyprofessors.com/professor/2924874", "type": "review" }, { "instructor_name": "Laurel Ohm", "review_date": "2024-12-15 05:43:44 +0000 UTC", "review_id": "bc0f8ed994ab66f73a7c7e05", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2924874", "source_review_id": "UmF0aW5nLTQwMzA1NjQw", "source_url": "https://www.ratemyprofessors.com/professor/2924874", "type": "review" }, { "instructor_name": "Chris Rycroft", "review_date": "2025-04-30 05:10:58 +0000 UTC", "review_id": "fc134d87a7c193849b54c10f", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2868294", "source_review_id": "UmF0aW5nLTQxMDk3MTY2", "source_url": "https://www.ratemyprofessors.com/professor/2868294", "type": "review" } ] } ``` #### offered true #### profile hash e59ddc7389015d0035b68cd195c939d475bf72b959b29cf12eab59b454ccaef1 #### quick take Qin Li receives consistent praise for clear lectures, approachability, and helpful office hours, though one review notes the class material is extensive and the course itself is tough. ```json { "citations": [ { "instructor_name": "Qin Li", "review_date": "2015-12-22 13:26:02 +0000 UTC", "review_id": "dc4bd03251aa3769c2e7e3d1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI1ODAyMDYz", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2017-01-18 16:08:45 +0000 UTC", "review_id": "b548c2047381f6f62e056453", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI3NzQ5Nzg5", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2018-12-31 01:15:28 +0000 UTC", "review_id": "74adc4040ee9f474c8ad9b38", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMxMTc4MzI0", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2019-01-29 16:43:17 +0000 UTC", "review_id": "d02b5f419b12026501d4f11f", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMxMzE2MzQy", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2020-05-03 21:15:27 +0000 UTC", "review_id": "f3192ba4974064931f744dbf", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMzMTkwNzE0", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2024-06-01 02:14:34 +0000 UTC", "review_id": "76c06214e8007d6af932ae74", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTM5NTQwNzQ2", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" } ] } ``` Recent recorded grades — Spring 2025: 3.40 GPA, 66.7% A/AB (n=30 letter grades); Fall 2025: 3.57 GPA, 71.7% A/AB (n=46 letter grades); Spring 2026: 3.77 GPA, 95.2% A/AB (n=42 letter grades). ```json { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience Students value Qin Li's clear explanations, exam guidance, and accessibility, finding her kind and helpful, while one reviewer highlights her inspirational and research-oriented teaching style. ```json { "citations": [ { "instructor_name": "Qin Li", "review_date": "2015-12-22 13:26:02 +0000 UTC", "review_id": "dc4bd03251aa3769c2e7e3d1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI1ODAyMDYz", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2017-01-18 16:08:45 +0000 UTC", "review_id": "b548c2047381f6f62e056453", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTI3NzQ5Nzg5", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2020-05-03 21:15:27 +0000 UTC", "review_id": "f3192ba4974064931f744dbf", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTMzMTkwNzE0", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" }, { "instructor_name": "Qin Li", "review_date": "2024-06-01 02:14:34 +0000 UTC", "review_id": "76c06214e8007d6af932ae74", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2059558", "source_review_id": "UmF0aW5nLTM5NTQwNzQ2", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history CHENXI WU is recorded teaching in Fall 2020. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" } ] } ``` CHRIS RYCROFT is recorded teaching in Spring 2023. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" } ] } ``` LAUREL OHM is recorded teaching in Fall 2024, Spring 2025, Fall 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ] } ``` QIN LI is recorded teaching in Fall 2015, Fall 2016, Fall 2018, Fall 2020, Spring 2024. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1162", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1172", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1192", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1192", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" } ] } ``` SAVERIO SPAGNOLIE is recorded teaching in Fall 2017, Fall 2019, Fall 2021, Fall 2022, Fall 2023. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1182", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1202", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "COMPSCI/MATH 514", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "source_record": { "entity_id": "2d69544c-2270-33fa-bee5-fbd76b1e2df0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [ "n1", "n19", "n20" ], "condition": null, "course": null, "evidence": "(MATH 320,340,341,345, or375), (MATH 322,341,375,421, or521), and (COMP SCI 200,220,300, or placement intoCOMP SCI 300), graduate/professional standing, or declared in Mathematics VISP (undergraduate or graduate)", "id": "n0", "kind": "all" }, { "children": [ "n2", "n8", "n14" ], "condition": null, "course": null, "evidence": "(MATH 320,340,341,345, or375), (MATH 322,341,375,421, or521), and (COMP SCI 200,220,300, or placement intoCOMP SCI 300)", "id": "n1", "kind": "any" }, { "children": [ "n3", "n4", "n5", "n6", "n7" ], "condition": null, "course": null, "evidence": "(MATH 320,340,341,345, or375)", "id": "n2", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 320, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "MATH 320", "id": "n3", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 340, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "340", "id": "n4", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 341, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "341", "id": "n5", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 345, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "345", "id": "n6", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 375, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "375", "id": "n7", "kind": "course" }, { "children": [ "n9", "n10", "n11", "n12", "n13" ], "condition": null, "course": null, "evidence": "(MATH 322,341,375,421, or521)", "id": "n8", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 322, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "322", "id": "n9", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 341, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "341", "id": "n10", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 375, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "375", "id": "n11", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 421, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "421", "id": "n12", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 521, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "521", "id": "n13", "kind": "course" }, { "children": [ "n15", "n16", "n17", "n18" ], "condition": null, "course": null, "evidence": "(COMP SCI 200,220,300, or placement intoCOMP SCI 300)", "id": "n14", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 200, "minimum_grade": null, "subjects": [ "COMPSCI" ], "timing": "prior" }, "evidence": "COMP SCI 200", "id": "n15", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 220, "minimum_grade": null, "subjects": [ "COMPSCI" ], "timing": "prior" }, "evidence": "220", "id": "n16", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 300, "minimum_grade": null, "subjects": [ "COMPSCI" ], "timing": "prior" }, "evidence": "COMP SCI 300", "id": "n17", "kind": "course" }, { "children": [], "condition": "placement intoCOMP SCI 300", "course": null, "evidence": "placement intoCOMP SCI 300", "id": "n18", "kind": "condition" }, { "children": [], "condition": "graduate/professional standing", "course": null, "evidence": "graduate/professional standing", "id": "n19", "kind": "condition" }, { "children": [], "condition": "declared in Mathematics VISP (undergraduate or graduate)", "course": null, "evidence": "declared in Mathematics VISP (undergraduate or graduate)", "id": "n20", "kind": "condition" } ] ``` #### notes * MATH 341 and MATH 375 appear in both Math requirement groups (n2 and n8). * COMPSCI 300 is linked in linked\_courses but requires placement test verification. * MATH 320, MATH 322, MATH 421, MATH 521 are linked in linked\_courses. * Ambiguity in whether the three main groups are ANDed or if they form a larger ANY set. #### root n0 #### status needs\_review ### instructors ```json [ { "instructor_uid": "instructor_ab5c68c5e0b538ecb5a4949f", "source": "enrollment", "source_instructor_id": "qli36", "identity_basis": "netid", "identity_status": "source_identified", "name": "Qin Li", "email": "QINLI@MATH.WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 28, "quality": 3.79, "difficulty": 3.11, "quality_count": 28, "difficulty_count": 28, "profile_id": "rmp:2059558", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "match_basis": "exact_name", "observed_at": "2026-09-07 16:11:25.404917+00:00", "courses": { "course_cc1de60e9953cdd9c469e9a5": { "review_count": 6, "quality": 3.17, "difficulty": 2.83, "quality_count": 6, "difficulty_count": 6 }, "course_f237678d9fac59631b4aa4ff": { "review_count": 6, "quality": 5, "difficulty": 3.5, "quality_count": 6, "difficulty_count": 6 }, "course_0002a781bc9543f3a2ac1a94": { "review_count": 16, "quality": 3.56, "difficulty": 3.06, "quality_count": 16, "difficulty_count": 16 } }, "bayesian_quality": 3.7357024098110814, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/QIN_LI" } ] ``` ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:266:004270", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1272", "source_course_id": "004270", "source_subject_id": "266", "title": "Numerical Analysis", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:600:004270", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1272", "source_course_id": "004270", "source_subject_id": "600", "title": "Numerical Analysis", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:16076", "term_id": "1272", "source_section_id": "16076", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 60, "enrolled": 13, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:16073", "term_id": "1272", "source_section_id": "16073", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 60, "enrolled": 43, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" } ] ``` ### grade instructors ```json [ { "instructor_uid": "instructor_948a42af0cbdec970eeadf81", "source": "madgrades", "source_instructor_id": "3998956", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JAMES A ROSSMANITH", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 2.812, "graded": 820, "counts": [ 202, 110, 172, 93, 153, 58, 32 ], "sections": 26 }, "instructor_url": "/instructors/JAMES_A_ROSSMANITH--instructor_948a42af0cbdec970eeadf81" }, { "instructor_uid": "instructor_b8e44b154dc09c12ff6006ac", "source": "madgrades", "source_instructor_id": "4101295", "identity_basis": "source_id", "identity_status": "source_identified", "name": "GHEORGHE CRACIUN", "email": null, "first_observed_at": "2026-09-06 23:14:58.172943+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "grade_statistics": { "gpa": 3.303, "graded": 1639, "counts": [ 909, 155, 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"2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "ratings": { "review_count": 28, "quality": 3.79, "difficulty": 3.11, "quality_count": 28, "difficulty_count": 28, "profile_id": "rmp:2059558", "source_url": "https://www.ratemyprofessors.com/professor/2059558", "match_basis": "exact_name", "observed_at": "2026-09-07 16:11:25.404917+00:00", "courses": { "course_cc1de60e9953cdd9c469e9a5": { "review_count": 6, "quality": 3.17, "difficulty": 2.83, "quality_count": 6, "difficulty_count": 6 }, "course_f237678d9fac59631b4aa4ff": { "review_count": 6, "quality": 5, "difficulty": 3.5, "quality_count": 6, "difficulty_count": 6 }, "course_0002a781bc9543f3a2ac1a94": { "review_count": 16, "quality": 3.56, "difficulty": 3.06, "quality_count": 16, "difficulty_count": 16 } }, "bayesian_quality": 3.7357024098110814, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/QIN_LI" } ] ``` ### grades ```json [ { "run_id": 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514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1192", "term_name": "Fall 2018", "instructors": [ "Qin Li" ], "a": 25, "ab": 23, "b": 20, "bc": 21, "c": 8, "d": 7, "f": 2, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 106, "source_aliases": [ "COMPSCI/MATH 514" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1202", "term_name": "Fall 2019", "instructors": [ "JORIS ROOS", "Saverio Spagnolie" ], "a": 21, "ab": 16, "b": 19, "bc": 13, "c": 8, "d": 1, "f": 3, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 81, "source_aliases": [ "COMPSCI/MATH 514" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": 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0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 47, "source_aliases": [ "COMPSCI/MATH 514" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Laurel Ohm" ], "a": 18, "ab": 5, "b": 7, "bc": 3, "c": 5, "d": 2, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 2, "total": 43, "source_aliases": [ "COMPSCI/MATH 514" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Laurel Ohm" ], "a": 15, "ab": 5, "b": 6, "bc": 1, "c": 2, "d": 0, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 2, "not_reported": 1, "other": 0, "total": 34, "source_aliases": [ "COMPSCI/MATH 514" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Laurel Ohm" ], "a": 25, "ab": 8, "b": 9, "bc": 2, "c": 2, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 47, "source_aliases": [ "COMPSCI/MATH 514" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/MATH 514", "course_uid": "course_f237678d9fac59631b4aa4ff", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "YASSINE TISSAOUI" ], "a": 27, "ab": 13, "b": 1, "bc": 0, "c": 1, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 1, "not_reported": 0, "other": 0, "total": 43, "source_aliases": [ "COMPSCI/MATH 514" ] } ] ``` ### statistics #### gpa 3.109 #### graded 980 #### counts * 332 * 172 * 195 * 112 * 104 * 44 * 21 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_f237678d9fac59631b4aa4ff-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_f237678d9fac59631b4aa4ff-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_f237678d9fac59631b4aa4ff-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_f237678d9fac59631b4aa4ff-0.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_f237678d9fac59631b4aa4ff-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_f237678d9fac59631b4aa4ff-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_f237678d9fac59631b4aa4ff-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_f237678d9fac59631b4aa4ff-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_f237678d9fac59631b4aa4ff-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_f237678d9fac59631b4aa4ff-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.1091836734693876 #### count 980 #### university ##### size 5165 ##### gpa Percentile 4 ##### count Percentile 87 ##### median Count 178 ##### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 10 | false | | 2.8–3.2 | 328 | true | | 3.2–3.6 | 1381 | false | | 3.6–4.0 | 3446 | false | #### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 108, "gpaPercentile": 7, "countPercentile": 71, "medianCount": 457, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 15, "current": true }, { "range": "3.2–3.6", "count": 31, "current": false }, { "range": "3.6–4.0", "count": 62, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 124, "gpaPercentile": 20, "countPercentile": 79, "medianCount": 181, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 4, "current": false }, { "range": "2.8–3.2", "count": 32, "current": true }, { "range": "3.2–3.6", "count": 25, "current": false }, { "range": "3.6–4.0", "count": 63, "current": false } ] } } ] ``` ### terms #### 1082 ##### term 1082 ##### gpa 3.480769230769231 ##### count 26 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1092 ##### term 1092 ##### gpa 3.25 ##### count 14 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1102 ##### term 1102 ##### gpa 3.3666666666666667 ##### count 30 ##### university ###### size 774 ###### gpa Percentile 52 ###### count Percentile 0 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 1 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 49 | false | | 2.8–3.2 | 201 | false | | 3.2–3.6 | 287 | true | | 3.6–4.0 | 235 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 19, "gpaPercentile": 72, "countPercentile": 0, "medianCount": 61, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 2, "current": false }, { "range": "2.8–3.2", "count": 9, "current": false }, { "range": "3.2–3.6", "count": 7, "current": true }, { "range": "3.6–4.0", "count": 1, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 27, "gpaPercentile": 92, "countPercentile": 0, "medianCount": 76, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 8, "current": false }, { "range": "2.8–3.2", "count": 11, "current": false }, { "range": "3.2–3.6", "count": 7, "current": true }, { "range": "3.6–4.0", "count": 0, "current": false } ] } } ] ``` #### 1112 ##### term 1112 ##### gpa 3.6666666666666665 ##### count 33 ##### university ###### size 805 ###### gpa Percentile 77 ###### count Percentile 7 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 45 | false | | 2.8–3.2 | 218 | false | | 3.2–3.6 | 316 | false | | 3.6–4.0 | 225 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 27, "gpaPercentile": 85, "countPercentile": 12, "medianCount": 41, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 6, "current": true } ] } }, { "subject": "MATH", "comparison": { "size": 26, "gpaPercentile": 100, "countPercentile": 8, "medianCount": 87, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 7, "current": false }, { "range": "2.8–3.2", "count": 12, "current": false }, { "range": "3.2–3.6", "count": 5, "current": false }, { "range": "3.6–4.0", "count": 1, "current": true } ] } } ] ``` #### 1122 ##### term 1122 ##### gpa 3.227272727272727 ##### count 22 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1132 ##### term 1132 ##### gpa 3.8333333333333335 ##### count 6 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1142 ##### term 1142 ##### gpa 2.75 ##### count 18 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1152 ##### term 1152 ##### gpa 2.6666666666666665 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1162 ##### term 1162 ##### gpa 2.985294117647059 ##### count 34 ##### university ###### size 954 ###### gpa Percentile 12 ###### count Percentile 8 ###### median Count 64.5 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 23 | false | | 2.8–3.2 | 234 | true | | 3.2–3.6 | 350 | false | | 3.6–4.0 | 345 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 35, "gpaPercentile": 15, "countPercentile": 0, "medianCount": 56, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 14, "current": true }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 11, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 36, "gpaPercentile": 40, "countPercentile": 9, "medianCount": 74.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 3, "current": false }, { "range": "2.8–3.2", "count": 20, "current": true }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } } ] ``` #### 1172 ##### term 1172 ##### gpa 3 ##### count 51 ##### university ###### size 991 ###### gpa Percentile 10 ###### count Percentile 35 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 22 | false | | 2.8–3.2 | 226 | true | | 3.2–3.6 | 353 | false | | 3.6–4.0 | 390 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 31, "gpaPercentile": 13, "countPercentile": 17, "medianCount": 74, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 16, "current": true }, { "range": "3.2–3.6", "count": 6, "current": false }, { "range": "3.6–4.0", "count": 9, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 36, "gpaPercentile": 49, "countPercentile": 26, "medianCount": 66, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 4, "current": false }, { "range": "2.8–3.2", "count": 21, "current": true }, { "range": "3.2–3.6", "count": 8, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } } ] ``` #### 1182 ##### term 1182 ##### gpa 3.041095890410959 ##### count 73 ##### university ###### size 1025 ###### gpa Percentile 14 ###### count Percentile 53 ###### median Count 69 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 21 | false | | 2.8–3.2 | 216 | true | | 3.2–3.6 | 369 | false | | 3.6–4.0 | 418 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 36, "gpaPercentile": 29, "countPercentile": 43, "medianCount": 90.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 13, "current": true }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 11, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 36, "gpaPercentile": 63, "countPercentile": 43, "medianCount": 80, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 5, "current": false }, { "range": "2.8–3.2", "count": 21, "current": true }, { "range": "3.2–3.6", "count": 7, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } } ] ``` #### 1192 ##### term 1192 ##### gpa 2.981132075471698 ##### count 106 ##### university ###### size 1077 ###### gpa Percentile 8 ###### count Percentile 71 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 22 | false | | 2.8–3.2 | 203 | true | | 3.2–3.6 | 370 | false | | 3.6–4.0 | 481 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 38, "gpaPercentile": 14, "countPercentile": 59, "medianCount": 95.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 15, "current": true }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 12, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 39, "gpaPercentile": 34, "countPercentile": 58, "medianCount": 99, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 4, "current": false }, { "range": "2.8–3.2", "count": 24, "current": true }, { "range": "3.2–3.6", "count": 8, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } } ] ``` #### 1202 ##### term 1202 ##### gpa 3.04320987654321 ##### count 81 ##### university ###### size 1102 ###### gpa Percentile 10 ###### count Percentile 59 ###### median Count 68 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 14 | false | | 2.8–3.2 | 218 | true | | 3.2–3.6 | 371 | false | | 3.6–4.0 | 498 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 41, "gpaPercentile": 13, "countPercentile": 45, "medianCount": 91, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 13, "current": true }, { "range": "3.2–3.6", "count": 15, "current": false }, { "range": "3.6–4.0", "count": 11, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 40, "gpaPercentile": 44, "countPercentile": 46, "medianCount": 90.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 4, "current": false }, { "range": "2.8–3.2", "count": 24, "current": true }, { "range": "3.2–3.6", "count": 7, "current": false }, { "range": "3.6–4.0", "count": 5, "current": false } ] } } ] ``` #### 1212 ##### term 1212 ##### gpa 2.922680412371134 ##### count 97 ##### university ###### size 1111 ###### gpa Percentile 2 ###### count Percentile 65 ###### median Count 68 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 4 | false | | 2.8–3.2 | 159 | true | | 3.2–3.6 | 337 | false | | 3.6–4.0 | 611 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 42, "gpaPercentile": 7, "countPercentile": 51, "medianCount": 96, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 12, "current": true }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 14, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 41, "gpaPercentile": 13, "countPercentile": 55, "medianCount": 87, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 2, "current": false }, { "range": "2.8–3.2", "count": 18, "current": true }, { "range": "3.2–3.6", "count": 12, "current": false }, { "range": "3.6–4.0", "count": 9, "current": false } ] } } ] ``` #### 1222 ##### term 1222 ##### gpa 2.9895833333333335 ##### count 48 ##### university ###### size 1157 ###### gpa Percentile 5 ###### count Percentile 34 ###### median Count 64 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 174 | true | | 3.2–3.6 | 351 | false | | 3.6–4.0 | 614 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 46, "gpaPercentile": 4, "countPercentile": 16, "medianCount": 94.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 8, "current": true }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 14, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 39, "gpaPercentile": 26, "countPercentile": 21, "medianCount": 63, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 5, "current": false }, { "range": "2.8–3.2", "count": 13, "current": true }, { "range": "3.2–3.6", "count": 12, "current": false }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1232 ##### term 1232 ##### gpa 2.9431818181818183 ##### count 44 ##### university ###### size 1216 ###### gpa Percentile 4 ###### count Percentile 28 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 14 | false | | 2.8–3.2 | 174 | true | | 3.2–3.6 | 356 | false | | 3.6–4.0 | 670 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 50, "gpaPercentile": 2, "countPercentile": 10, "medianCount": 82.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 9, "current": true }, { "range": "3.2–3.6", "count": 19, "current": false }, { "range": "3.6–4.0", "count": 22, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 43, "gpaPercentile": 17, "countPercentile": 31, "medianCount": 69, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 4, "current": false }, { "range": "2.8–3.2", "count": 17, "current": true }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 7, "current": false } ] } } ] ``` #### 1234 ##### term 1234 ##### gpa 2.972972972972973 ##### count 37 ##### university ###### size 1188 ###### gpa Percentile 5 ###### count Percentile 15 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 3 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 144 | true | | 3.2–3.6 | 374 | false | | 3.6–4.0 | 650 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 46, "gpaPercentile": 2, "countPercentile": 16, "medianCount": 111, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 8, "current": true }, { "range": "3.2–3.6", "count": 26, "current": false }, { "range": "3.6–4.0", "count": 12, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 41, "gpaPercentile": 33, "countPercentile": 23, "medianCount": 67, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 2, "current": false }, { "range": "2.4–2.8", "count": 5, "current": false }, { "range": "2.8–3.2", "count": 13, "current": true }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 7, "current": false } ] } } ] ``` #### 1242 ##### term 1242 ##### gpa 2.8703703703703702 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | COMPSCI | | | MATH | | #### 1244 ##### term 1244 ##### gpa 2.893617021276596 ##### count 47 ##### university ###### size 1241 ###### gpa Percentile 2 ###### count Percentile 32 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 9 | false | | 2.8–3.2 | 151 | true | | 3.2–3.6 | 373 | false | | 3.6–4.0 | 706 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 46, "gpaPercentile": 0, "countPercentile": 13, "medianCount": 116, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 11, "current": true }, { "range": "3.2–3.6", "count": 17, "current": false }, { "range": "3.6–4.0", "count": 18, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 43, "gpaPercentile": 12, "countPercentile": 33, "medianCount": 68, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 2, "current": false }, { "range": "2.4–2.8", "count": 2, "current": false }, { "range": "2.8–3.2", "count": 20, "current": true }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1252 ##### term 1252 ##### gpa 3.1707317073170733 ##### count 41 ##### university ###### size 1333 ###### gpa Percentile 8 ###### count Percentile 23 ###### median Count 69 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 14 | false | | 2.8–3.2 | 115 | true | | 3.2–3.6 | 431 | false | | 3.6–4.0 | 773 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 54, "gpaPercentile": 13, "countPercentile": 21, "medianCount": 101, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 8, "current": true }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 22, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 43, "gpaPercentile": 50, "countPercentile": 19, "medianCount": 74, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 5, "current": false }, { "range": "2.8–3.2", "count": 20, "current": true }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 2, "current": false } ] } } ] ``` #### 1254 ##### term 1254 ##### gpa 3.4 ##### count 30 ##### university ###### size 1289 ###### gpa Percentile 24 ###### count Percentile 0 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 128 | false | | 3.2–3.6 | 379 | true | | 3.6–4.0 | 765 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 52, "gpaPercentile": 37, "countPercentile": 0, "medianCount": 105, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 24, "current": true }, { "range": "3.6–4.0", "count": 17, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 39, "gpaPercentile": 76, "countPercentile": 0, "medianCount": 89, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 6, "current": false }, { "range": "2.8–3.2", "count": 16, "current": false }, { "range": "3.2–3.6", "count": 13, "current": true }, { "range": "3.6–4.0", "count": 4, "current": false } ] } } ] ``` #### 1262 ##### term 1262 ##### gpa 3.5652173913043477 ##### count 46 ##### university ###### size 1320 ###### gpa Percentile 36 ###### count Percentile 28 ###### median Count 70 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 8 | false | | 2.8–3.2 | 133 | false | | 3.2–3.6 | 381 | true | | 3.6–4.0 | 797 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 53, "gpaPercentile": 52, "countPercentile": 15, "medianCount": 82, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 22, "current": true }, { "range": "3.6–4.0", "count": 21, "current": false } ] } }, { "subject": "MATH", "comparison": { "size": 43, "gpaPercentile": 83, "countPercentile": 24, "medianCount": 81, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 3, "current": false }, { "range": "2.8–3.2", "count": 18, "current": false }, { "range": "3.2–3.6", "count": 16, "current": true }, { "range": "3.6–4.0", "count": 6, "current": false } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.7738095238095237 ##### count 42 ##### university ###### size 1283 ###### gpa Percentile 60 ###### count Percentile 24 ###### median Count 66 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 20 | false | | 2.8–3.2 | 130 | false | | 3.2–3.6 | 343 | false | | 3.6–4.0 | 789 | true | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 48, "gpaPercentile": 77, "countPercentile": 13, "medianCount": 105.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 7, "current": false }, { "range": "3.2–3.6", "count": 21, "current": false }, { "range": "3.6–4.0", "count": 19, "current": true } ] } }, { "subject": "MATH", "comparison": { "size": 42, "gpaPercentile": 93, "countPercentile": 22, "medianCount": 80, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 1, "current": false }, { "range": "2.4–2.8", "count": 7, "current": false }, { "range": "2.8–3.2", "count": 17, "current": false }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 6, "current": true } ] } } ] ``` ### benchmarks #### all ##### school ###### size 5165 ###### gpa 3.6768522900967713 ###### top Share 82.85737869901621 ###### count 178 ##### COMPSCI ###### size 108 ###### gpa 3.587463041575572 ###### top Share 78.48078155181335 ###### count 457 ##### MATH ###### size 124 ###### gpa 3.535885596153481 ###### top Share 74.29566602021787 ###### count 181 #### terms ##### 1082 ###### school ###### size 723 ###### gpa 3.3583896732335172 ###### top Share 62.932746798940194 ###### count 68 ###### COMPSCI ###### size 15 ###### gpa 3.146224995259422 ###### top Share 51.28801425895212 ###### count 49 ###### MATH ###### size 20 ###### gpa 2.8603540012311925 ###### top Share 39.28661748894661 ###### count 122 ##### 1092 ###### school ###### size 732 ###### gpa 3.374660709520374 ###### top Share 63.690339324346596 ###### count 70 ###### COMPSCI ###### size 16 ###### gpa 3.14888347660136 ###### top Share 52.49548911325188 ###### count 66.5 ###### MATH ###### size 22 ###### gpa 2.8820162698417926 ###### top Share 39.71597770466243 ###### count 131 ##### 1102 ###### school ###### size 774 ###### gpa 3.36712622366007 ###### top Share 63.703228532165696 ###### count 67 ###### COMPSCI ###### size 19 ###### gpa 3.1851402069816737 ###### top Share 53.3667497934056 ###### count 61 ###### MATH ###### size 27 ###### gpa 2.936619140855453 ###### top Share 42.28372460948232 ###### count 76 ##### 1112 ###### school ###### size 805 ###### gpa 3.3737773184830386 ###### top Share 63.91039244872789 ###### count 66 ###### COMPSCI ###### size 27 ###### gpa 3.2907039795974518 ###### top Share 61.485726181424475 ###### count 41 ###### MATH ###### size 26 ###### gpa 2.9941347625171355 ###### top Share 43.79682105650899 ###### count 87 ##### 1122 ###### school ###### size 804 ###### gpa 3.3737149752667013 ###### top Share 63.65118790117902 ###### count 70 ###### COMPSCI ###### size 20 ###### gpa 3.20674670802027 ###### top Share 56.51588103392879 ###### count 54.5 ###### MATH ###### size 27 ###### gpa 2.898067749128924 ###### top Share 42.09489165698714 ###### count 103 ##### 1132 ###### school ###### size 851 ###### gpa 3.391128778809763 ###### top Share 64.69509437122704 ###### count 66 ###### COMPSCI ###### size 23 ###### gpa 3.2325357852525465 ###### top Share 57.33650851473996 ###### count 56 ###### MATH ###### size 25 ###### gpa 2.9605395515107897 ###### top Share 42.794601137643824 ###### count 108 ##### 1142 ###### school ###### size 853 ###### gpa 3.3941849959684913 ###### top Share 65.28450334228523 ###### count 67 ###### COMPSCI ###### size 28 ###### gpa 3.279575360328891 ###### top Share 60.13197427273153 ###### count 47.5 ###### MATH ###### size 31 ###### gpa 3.009040780059457 ###### top Share 45.87481076818359 ###### count 77 ##### 1152 ###### school ###### size 918 ###### gpa 3.408733538594633 ###### top Share 66.06693005846735 ###### count 65 ###### COMPSCI ###### size 30 ###### gpa 3.3169698368361287 ###### top Share 64.20051564737066 ###### count 48.5 ###### MATH ###### size 34 ###### gpa 3.0803080141506425 ###### top Share 49.72677618758506 ###### count 82 ##### 1162 ###### school ###### size 954 ###### gpa 3.43726781345039 ###### top Share 68.05645304987395 ###### count 64.5 ###### COMPSCI ###### size 35 ###### gpa 3.3323013900568625 ###### top Share 63.38685451839816 ###### count 56 ###### MATH ###### size 36 ###### gpa 3.1059509777204544 ###### top Share 50.071044743474 ###### count 74.5 ##### 1172 ###### school ###### size 991 ###### gpa 3.465129042641772 ###### top Share 69.42600667567366 ###### count 67 ###### COMPSCI ###### size 31 ###### gpa 3.3325489227746874 ###### top Share 61.97665055034616 ###### count 74 ###### MATH ###### size 36 ###### gpa 3.098601909983034 ###### top Share 48.67573746500224 ###### count 66 ##### 1182 ###### school ###### size 1025 ###### gpa 3.474159360325319 ###### top Share 70.34861441764347 ###### count 69 ###### COMPSCI ###### size 36 ###### gpa 3.352907303323745 ###### top Share 63.88103454195665 ###### count 90.5 ###### MATH ###### size 36 ###### gpa 3.0839531022443034 ###### top Share 48.116975859522796 ###### count 80 ##### 1192 ###### school ###### size 1077 ###### gpa 3.50327634323125 ###### top Share 72.44641925727845 ###### count 67 ###### COMPSCI ###### size 38 ###### gpa 3.3453717241366854 ###### top Share 64.2917310505246 ###### count 95.5 ###### MATH ###### size 39 ###### gpa 3.1003216533236415 ###### top Share 50.01588968281552 ###### count 99 ##### 1202 ###### school ###### size 1102 ###### gpa 3.5102605987403313 ###### top Share 72.78244569053733 ###### count 68 ###### COMPSCI ###### size 41 ###### gpa 3.3598624373657553 ###### top Share 65.26544910639922 ###### count 91 ###### MATH ###### size 40 ###### gpa 3.1467748801316944 ###### top Share 52.57847974231038 ###### count 90.5 ##### 1212 ###### school ###### size 1111 ###### gpa 3.5856416028074487 ###### top Share 77.58926748660845 ###### count 68 ###### COMPSCI ###### size 42 ###### gpa 3.450396020252364 ###### top Share 69.90950224603134 ###### count 96 ###### MATH ###### size 41 ###### gpa 3.3211331103538813 ###### top Share 59.85093623917685 ###### count 87 ##### 1222 ###### school ###### size 1157 ###### gpa 3.563052311875811 ###### top Share 76.64869058732418 ###### count 64 ###### COMPSCI ###### size 46 ###### gpa 3.4266761668874532 ###### top Share 68.93117403010548 ###### count 94.5 ###### MATH ###### size 39 ###### gpa 3.2083447119296955 ###### top Share 56.75007696473496 ###### count 63 ##### 1232 ###### school ###### size 1216 ###### gpa 3.575457431972425 ###### top Share 77.33712216234007 ###### count 66 ###### COMPSCI ###### size 50 ###### gpa 3.522872390836507 ###### top Share 74.11555010870671 ###### count 82.5 ###### MATH ###### size 43 ###### gpa 3.2486774162409366 ###### top Share 56.56203211471963 ###### count 69 ##### 1234 ###### school ###### size 1188 ###### gpa 3.5799441677552393 ###### top Share 77.18256448537606 ###### count 65 ###### COMPSCI ###### size 46 ###### gpa 3.457340982461054 ###### top Share 70.00975704504911 ###### count 111 ###### MATH ###### size 41 ###### gpa 3.178489266862151 ###### top Share 56.06874885619616 ###### count 67 ##### 1242 ###### school ###### size 1295 ###### gpa 3.595302892737449 ###### top Share 78.36291889885307 ###### count 67 ###### COMPSCI ###### size 52 ###### gpa 3.5206188715369935 ###### top Share 74.2043106737207 ###### count 99 ###### MATH ###### size 43 ###### gpa 3.2449031633350183 ###### top Share 58.03783489438137 ###### count 80 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### COMPSCI ###### size 46 ###### gpa 3.477413782571094 ###### top Share 70.8725394264854 ###### count 116 ###### MATH ###### size 43 ###### gpa 3.228240949537157 ###### top Share 55.86451059486035 ###### count 68 ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ###### COMPSCI ###### size 54 ###### gpa 3.5244021201456657 ###### top Share 75.07938169795783 ###### count 101 ###### MATH ###### size 43 ###### gpa 3.185692541204979 ###### top Share 54.14175342403773 ###### count 74 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### COMPSCI ###### size 52 ###### gpa 3.482652727664103 ###### top Share 71.33786483648515 ###### count 105 ###### MATH ###### size 39 ###### gpa 3.180435541912479 ###### top Share 53.878371816747475 ###### count 89 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### COMPSCI ###### size 53 ###### gpa 3.533845597774486 ###### top Share 75.31824598445624 ###### count 82 ###### MATH ###### size 43 ###### gpa 3.2481769276584003 ###### top Share 56.325967864851854 ###### count 81 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### COMPSCI ###### size 48 ###### gpa 3.5022746140005943 ###### top Share 73.13318776233326 ###### count 105.5 ###### MATH ###### size 42 ###### gpa 3.13598176627681 ###### top Share 52.25969905887213 ###### count 80 ## instructor Trends ```json [ { "uid": "instructor_6cee1ae6c2c6ae042c8870e4", "name": "QIN LI", "count": 288, "terms": [ { "term": "1162", "count": 34, "sections": 1, "gpa": 2.985294117647059 }, { "term": "1172", "count": 51, "sections": 1, "gpa": 3 }, { "term": "1192", "count": 106, "sections": 2, "gpa": 2.981132075471698 }, { "term": "1212", "count": 50, "sections": 1, "gpa": 2.94 }, { "term": "1244", "count": 47, "sections": 1, "gpa": 2.893617021276596 } ] }, { "uid": "instructor_ec22b3679a357165d2295d3a", "name": "SAVERIO SPAGNOLIE", "count": 235, "terms": [ { "term": "1182", "count": 73, "sections": 1, "gpa": 3.041095890410959 }, { "term": "1202", "count": 43, "sections": 1, "gpa": 2.9302325581395348 }, { "term": "1222", "count": 48, "sections": 2, "gpa": 2.9895833333333335 }, { "term": "1232", "count": 44, "sections": 1, "gpa": 2.9431818181818183 }, { "term": "1242", "count": 27, "sections": 1, "gpa": 2.8703703703703702 } ] }, { "uid": "instructor_e3bd9c96e72283399c239101", "name": "LAUREL OHM", "count": 117, "terms": [ { "term": "1252", "count": 41, "sections": 1, "gpa": 3.1707317073170733 }, { "term": "1254", "count": 30, "sections": 1, "gpa": 3.4 }, { "term": "1262", "count": 46, "sections": 1, "gpa": 3.5652173913043477 } ] }, { "uid": "instructor_948a42af0cbdec970eeadf81", "name": "JAMES A ROSSMANITH", "count": 70, "terms": [ { "term": "1082", "count": 26, "sections": 1, "gpa": 3.480769230769231 }, { "term": "1092", "count": 14, "sections": 1, "gpa": 3.25 }, { "term": "1102", "count": 30, "sections": 1, "gpa": 3.3666666666666667 } ] }, { "uid": "instructor_2fcd8ca860c9e8174b0b4bd0", "name": "SHI JIN", "count": 67, "terms": [ { "term": "1122", "count": 22, "sections": 1, "gpa": 3.227272727272727 }, { "term": "1142", "count": 18, "sections": 1, "gpa": 2.75 }, { "term": "1152", "count": 27, "sections": 1, "gpa": 2.6666666666666665 } ] }, { "uid": "instructor_09b1c1be00e1b7fd397c55cf", "name": "CHENXI WU", "count": 47, "terms": [ { "term": "1212", "count": 47, "sections": 1, "gpa": 2.904255319148936 } ] }, { "uid": "instructor_5ef0dd436ef3a17c11ba1768", "name": "YASSINE TISSAOUI", "count": 42, "terms": [ { "term": "1264", "count": 42, "sections": 1, "gpa": 3.7738095238095237 } ] }, { "uid": "instructor_e7f5b56a6a8a98bb445c6baa", "name": "JORIS ROOS", "count": 38, "terms": [ { "term": "1202", "count": 38, "sections": 1, "gpa": 3.1710526315789473 } ] }, { "uid": "instructor_1afc370e7c2e6fa6c62774f8", "name": "CHRIS RYCROFT", "count": 37, "terms": [ { "term": "1234", "count": 37, "sections": 1, "gpa": 2.972972972972973 } ] }, { "uid": "instructor_b8e44b154dc09c12ff6006ac", "name": "GHEORGHE CRACIUN", "count": 33, "terms": [ { "term": "1112", "count": 33, "sections": 1, "gpa": 3.6666666666666665 } ] }, { "uid": "instructor_6312a86f24fae1d57d2fa787", "name": "YONGYONG CAI", "count": 6, "terms": [ { "term": "1132", "count": 6, "sections": 1, "gpa": 3.8333333333333335 } ] } ] ``` ## following None recorded.