# STAT 628: Data Science Practicum | UW–Madison [View on UW Courses](https://uwcourses.com/courses/STAT_628) ## 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 e561117e858a7267fdda90d1bd28493c64eeff07aee559ff6cf6bff3d0bf9f0f ### course id STAT 628 ### course uid course\_dec5d5852b060024b87f5ac8 ### catalog version id dffbcd0402e647537211994f6d504e08c516e80030a88d1c0b4e18adf31fa286 ### course number 628 ### subjects * STAT ### title DATA SCIENCE PRACTICUM ### description Provides an understanding of and experience with turning statistics concepts into practice through data science practicums inspired by realistic projects. Combine theory and methods expertise with communications skills to translate from a vaguely stated project description and complex data set into a concisely summarized analysis, including both written and graphical interpretation that can be used by decision makers in an organization. ### requirements text Declared in Statistics: Statistics and Data Science MS ### credits min 3 ### credits max 3 ### credit offering ids * 1272:932:024364 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 13c4718399b085b8b35f8f2efd1bdd9688d958496d62e039f01b5ad3d542314b ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary STAT 628 DATA SCIENCE PRACTICUM turns statistics concepts into practice through data science practicums inspired by realistic projects. ### llm topics * Data science practicums * Complex data sets * Graphical interpretation ### llm skills * Communications skills for data science * Translating project descriptions and complex data into summarized analysis * Written and graphical interpretation for decision makers ### llm assumed background None recorded. ### llm search phrases * data science practicum * STAT 628 statistics practice * data analysis communication * statistical interpretation graphs ### llm requirements status valid ### llm student summary status valid ### llm experience status valid ### catalog variants None recorded. ### student summary #### context hash a4898dff03dc4b5c1dd73a877904e40cd7b577932639e7d2d606cf03dabf4e8b #### course id STAT 628 #### current instructors ```json [ { "instructor_uid": "instructor_4cd2130743ca159fa112f0bd", "message": "No course-specific reviews available", "name": "Bret Larget", "review_status": "no_course_reviews", "rmp_instructor_id": "rmp:566625", "summary": [] }, { "instructor_uid": "instructor_78816c3a97b88702c28f569f", "message": "No course-specific reviews available", "name": "Zhanpeng Xu", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [] } ] ``` #### difficulty workload Historical reviews of Hyunseung Kang: The class is a lot of work, with grades heavily dependent on randomly assigned group projects and unclear grading criteria. ```json { "citations": [ { "instructor_name": "Hyunseung Kang", "review_date": "2022-11-25 00:25:29 +0000 UTC", "review_id": "320ab5a52747a2d12f8627bb", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM2ODg5Njky", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2023-10-25 17:46:25 +0000 UTC", "review_id": "d45934441bd2c2affcaad463", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4MzA4NTg5", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2023-12-27 23:28:41 +0000 UTC", "review_id": "e8e123f510025ddf86cbc210", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4ODAxNDY0", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" } ] } ``` #### errors None recorded. #### historical context Historical reviews of Hyunseung Kang: Hyunseung Kang is described as beneficial for data science careers but criticized for rigid statistical preferences over machine learning. Reviewers report unclear grading criteria, unfair assessments based on randomized group projects, and a lack of explanatory feedback, creating significant frustration despite the course's potential utility. ```json { "citations": [ { "instructor_name": "Hyunseung Kang", "review_date": "2019-10-31 17:27:40 +0000 UTC", "review_id": "72ec682239d9559ba791b441", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTMyMzQyMDYx", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2022-11-25 00:25:29 +0000 UTC", "review_id": "320ab5a52747a2d12f8627bb", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM2ODg5Njky", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2023-10-25 17:46:25 +0000 UTC", "review_id": "d45934441bd2c2affcaad463", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4MzA4NTg5", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2023-10-25 18:49:57 +0000 UTC", "review_id": "33f99f8e6797bebae81ba4c7", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4MzA4OTMz", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2023-12-27 23:28:41 +0000 UTC", "review_id": "e8e123f510025ddf86cbc210", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4ODAxNDY0", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" } ] } ``` #### offered true #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Historical reviews of Hyunseung Kang: Hyunseung Kang's course is beneficial for data science careers but involves significant workload and program scheduling conflicts. ```json { "citations": [ { "instructor_name": "Hyunseung Kang", "review_date": "2019-10-31 17:27:40 +0000 UTC", "review_id": "72ec682239d9559ba791b441", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTMyMzQyMDYx", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2022-11-25 00:25:29 +0000 UTC", "review_id": "320ab5a52747a2d12f8627bb", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM2ODg5Njky", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" } ] } ``` Recent recorded grades — Spring 2025: 3.73 GPA, 84.6% A/AB (n=13 letter grades); Fall 2025: 3.72 GPA, 88.9% A/AB (n=18 letter grades); Spring 2026: 3.88 GPA, 100.0% A/AB (n=21 letter grades). ```json { "citations": [ { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience Historical reviews of Hyunseung Kang: Reviewers report Kang dislikes machine learning work, insisting on statistical answers, which limits learning for some students. ```json { "citations": [ { "instructor_name": "Hyunseung Kang", "review_date": "2023-10-25 17:46:25 +0000 UTC", "review_id": "d45934441bd2c2affcaad463", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4MzA4NTg5", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" }, { "instructor_name": "Hyunseung Kang", "review_date": "2023-10-25 18:49:57 +0000 UTC", "review_id": "33f99f8e6797bebae81ba4c7", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2234533", "source_review_id": "UmF0aW5nLTM4MzA4OTMz", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history HYUNSEUNG KANG is recorded teaching in Spring 2018, Spring 2019, Fall 2019, Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1184", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1194", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1202", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "STAT 628", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "source_record": { "entity_id": "74fb97c9-9e98-3e8a-b0d9-66123b5a8e33", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [], "condition": "Declared in Statistics: Statistics and Data Science MS", "course": null, "evidence": "Declared in Statistics: Statistics and Data Science MS", "id": "n0", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors ```json [ { "instructor_uid": "instructor_4cd2130743ca159fa112f0bd", "source": "enrollment", "source_instructor_id": "brlarget", "identity_basis": "netid", "identity_status": "source_identified", "name": "Bret Larget", "email": "BRET.LARGET@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": 29, "quality": 3.31, "difficulty": 3.21, "quality_count": 29, "difficulty_count": 29, "profile_id": "rmp:566625", "source_url": "https://www.ratemyprofessors.com/professor/566625", "match_basis": "exact_name", "observed_at": "2026-09-07 16:51:20.625013+00:00", "courses": { "course_03f8aaae24bac7658b319ca8": { "review_count": 16, "quality": 2.88, "difficulty": 3.31, "quality_count": 16, "difficulty_count": 16 }, "course_72cc7ddf48330b71523f309f": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_2a00c702ff402614a950606e": { "review_count": 2, "quality": 4, "difficulty": 2, "quality_count": 2, "difficulty_count": 2 }, "course_e593b86c370a0c671af794df": { "review_count": 1, "quality": 5, "difficulty": 5, "quality_count": 1, "difficulty_count": 1 }, "course_4dd38bb021601e5dff558ba1": { "review_count": 1, "quality": 2, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_31fb5b7b6bf20ca63e33bd46": { "review_count": 2, "quality": 4.5, "difficulty": 2, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.4527288912435083, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/BRET_LARGET" }, { "instructor_uid": "instructor_78816c3a97b88702c28f569f", "source": "enrollment", "source_instructor_id": "zxu555", "identity_basis": "netid", "identity_status": "source_identified", "name": "Zhanpeng Xu", "email": "ZXU555@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", "instructor_url": "/instructors/ZHANPENG_XU" } ] ``` ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:932:024364", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1272", "source_course_id": "024364", "source_subject_id": "932", "title": "Data Science Practicum", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall, Spring, Summer" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:20188", "term_id": "1272", "source_section_id": "20188", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 24, "enrolled": 18, "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_5983f7a189c2f65b2819f132", "source": "madgrades", "source_instructor_id": "2602055", "identity_basis": "source_id", "identity_status": "source_identified", "name": "BRIAN YANDELL", "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": 3.746, "graded": 167, "counts": [ 97, 55, 15, 0, 0, 0, 0 ], "sections": 51 }, "instructor_url": "/instructors/BRIAN_YANDELL--instructor_5983f7a189c2f65b2819f132" }, { "instructor_uid": "instructor_ac940d98fd555bfd1c37966e", "source": "madgrades", "source_instructor_id": "4734607", "identity_basis": "source_id", "identity_status": "source_identified", "name": "HYUNSEUNG KANG", "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", "ratings": { "review_count": 29, "quality": 3.52, "difficulty": 3.31, "quality_count": 29, "difficulty_count": 29, "profile_id": "rmp:2234533", "source_url": "https://www.ratemyprofessors.com/professor/2234533", "match_basis": "exact_name", "observed_at": "2026-09-07 16:36:17.327287+00:00", "courses": { "course_ef9c9cd4a7d8002288a4cf7c": { "review_count": 21, "quality": 3.48, "difficulty": 3.33, "quality_count": 21, "difficulty_count": 21 }, "course_dec5d5852b060024b87f5ac8": { "review_count": 5, "quality": 2.8, "difficulty": 3.4, "quality_count": 5, "difficulty_count": 5 }, "course_e593b86c370a0c671af794df": { "review_count": 2, "quality": 5, "difficulty": 3, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.5770146055292225, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.805, "graded": 944, "counts": [ 764, 91, 46, 24, 7, 5, 7 ], "sections": 43 }, "instructor_url": "/instructors/HYUNSEUNG_KANG--instructor_ac940d98fd555bfd1c37966e" }, { "instructor_uid": "instructor_9cc75f9b84f6da363f0b5fb0", "source": "madgrades", "source_instructor_id": "6088802", "identity_basis": "source_id", "identity_status": "source_identified", "name": "HANYING JIANG", "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": 3.995, "graded": 101, "counts": [ 100, 1, 0, 0, 0, 0, 0 ], "sections": 2 }, "instructor_url": "/instructors/HANYING_JIANG--instructor_9cc75f9b84f6da363f0b5fb0" }, { "instructor_uid": "instructor_bc7547c463578e6a6f5351b8", "source": "madgrades", "source_instructor_id": "6318178", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ZHIFENG CHEN", "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": 3.783, "graded": 1042, "counts": [ 814, 107, 64, 33, 16, 5, 3 ], "sections": 35 }, "instructor_url": "/instructors/ZHIFENG_CHEN--instructor_bc7547c463578e6a6f5351b8" }, { "instructor_uid": "instructor_71e12ad537764a7f7f348a74", "source": "madgrades", "source_instructor_id": "4472697", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SAMEER DESHPANDE", "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": 3.902, "graded": 351, "counts": [ 314, 18, 9, 7, 3, 0, 0 ], "sections": 23 }, "instructor_url": "/instructors/SAMEER_DESHPANDE--instructor_71e12ad537764a7f7f348a74" }, { "instructor_uid": "instructor_f239799e8b1d244fb8b0f240", "source": "madgrades", "source_instructor_id": "6208535", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SIXU LI", "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": 3.615, "graded": 394, "counts": [ 257, 44, 50, 23, 15, 5, 0 ], "sections": 13 }, "instructor_url": "/instructors/SIXU_LI--instructor_f239799e8b1d244fb8b0f240" }, { "instructor_uid": "instructor_706ebccaed66febaf1bfdfb7", "source": "madgrades", "source_instructor_id": "5966080", "identity_basis": "source_id", "identity_status": "source_identified", "name": "PAUL NGUYEN", "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": 3.536, "graded": 42, "counts": [ 16, 13, 13, 0, 0, 0, 0 ], "sections": 2 }, "instructor_url": "/instructors/PAUL_NGUYEN--instructor_706ebccaed66febaf1bfdfb7" }, { "instructor_uid": "instructor_4e7dcf69a8ea9529cddc6b67", "source": "madgrades", "source_instructor_id": "3955546", "identity_basis": "source_id", "identity_status": "source_identified", "name": "CECILE ANE", "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", "ratings": { "review_count": 9, "quality": 4.11, "difficulty": 3.11, "quality_count": 9, "difficulty_count": 9, "profile_id": "rmp:755215", "source_url": "https://www.ratemyprofessors.com/professor/755215", "match_basis": "exact_name", "observed_at": "2026-09-07 16:49:25.949068+00:00", "courses": { "course_72cc7ddf48330b71523f309f": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_62341da3d7cd1db5f9ca5903": { "review_count": 1, "quality": 4, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_e593b86c370a0c671af794df": { "review_count": 2, "quality": 4.5, "difficulty": 3, "quality_count": 2, "difficulty_count": 2 }, "course_31fb5b7b6bf20ca63e33bd46": { "review_count": 1, "quality": 4, "difficulty": 3, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7994384714114453, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.507, "graded": 1012, "counts": [ 428, 285, 239, 35, 16, 3, 6 ], "sections": 93 }, "instructor_url": "/instructors/CECILE_ANE--instructor_4e7dcf69a8ea9529cddc6b67" }, { "instructor_uid": "instructor_253cce0f28321f783c10482f", "source": "madgrades", "source_instructor_id": "6315818", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JESSI KEHE", "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": 3.576, "graded": 321, "counts": [ 170, 105, 16, 15, 7, 1, 7 ], "sections": 16 }, "instructor_url": "/instructors/JESSI_KEHE--instructor_253cce0f28321f783c10482f" }, { "instructor_uid": "instructor_4cd2130743ca159fa112f0bd", "source": "enrollment", "source_instructor_id": "brlarget", "identity_basis": "netid", "identity_status": "source_identified", "name": "Bret Larget", "email": "BRET.LARGET@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": 29, "quality": 3.31, "difficulty": 3.21, "quality_count": 29, "difficulty_count": 29, "profile_id": "rmp:566625", "source_url": "https://www.ratemyprofessors.com/professor/566625", "match_basis": "exact_name", "observed_at": "2026-09-07 16:51:20.625013+00:00", "courses": { "course_03f8aaae24bac7658b319ca8": { "review_count": 16, "quality": 2.88, "difficulty": 3.31, "quality_count": 16, "difficulty_count": 16 }, "course_72cc7ddf48330b71523f309f": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_2a00c702ff402614a950606e": { "review_count": 2, "quality": 4, "difficulty": 2, "quality_count": 2, "difficulty_count": 2 }, "course_e593b86c370a0c671af794df": { "review_count": 1, "quality": 5, "difficulty": 5, "quality_count": 1, "difficulty_count": 1 }, "course_4dd38bb021601e5dff558ba1": { "review_count": 1, "quality": 2, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_31fb5b7b6bf20ca63e33bd46": { "review_count": 2, "quality": 4.5, "difficulty": 2, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.4527288912435083, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/BRET_LARGET" }, { "instructor_uid": "instructor_78816c3a97b88702c28f569f", "source": "enrollment", "source_instructor_id": "zxu555", "identity_basis": "netid", "identity_status": "source_identified", "name": "Zhanpeng Xu", "email": "ZXU555@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", "instructor_url": "/instructors/ZHANPENG_XU" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1164", "term_name": "Spring 2016", "instructors": [ "Brian Yandell" ], "a": 12, "ab": 0, "b": 0, "bc": 0, "c": 0, "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": 13, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1184", "term_name": "Spring 2018", "instructors": [ "Hyunseung Kang" ], "a": 8, "ab": 26, "b": 11, "bc": 1, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 46, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1194", "term_name": "Spring 2019", "instructors": [ "Hyunseung Kang" ], "a": 33, "ab": 8, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 41, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1202", "term_name": "Fall 2019", "instructors": [ "Hyunseung Kang" ], "a": 73, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 73, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1212", "term_name": "Fall 2020", "instructors": [ "Hyunseung Kang" ], "a": 64, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 64, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1222", "term_name": "Fall 2021", "instructors": [ "Hyunseung Kang", "Wanting Jiang" ], "a": 38, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 38, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1232", "term_name": "Fall 2022", "instructors": [ "Hyunseung Kang", "Wanting Jiang" ], "a": 62, "ab": 1, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 63, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1234", "term_name": "Spring 2023", "instructors": [ "Brian Yandell" ], "a": 0, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 0, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1242", "term_name": "Fall 2023", "instructors": [ "Hyunseung Kang", "Zhifeng Chen" ], "a": 36, "ab": 11, "b": 2, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 49, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Sameer Deshpande", "Zhifeng Chen" ], "a": 9, "ab": 4, "b": 2, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 15, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Hyunseung Kang", "SIXU LI" ], "a": 34, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 34, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "PAUL NGUYEN", "Sameer Deshpande" ], "a": 8, "ab": 3, "b": 2, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 13, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Cecile Ane", "SIXU LI" ], "a": 10, "ab": 6, "b": 2, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 18, "source_aliases": [ "STAT 628" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 628", "course_uid": "course_dec5d5852b060024b87f5ac8", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Jessi Kehe", "SIXU LI" ], "a": 16, "ab": 5, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 21, "source_aliases": [ "STAT 628" ] } ] ``` ### statistics #### gpa 3.892 #### graded 487 #### counts * 403 * 64 * 19 * 1 * 0 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_dec5d5852b060024b87f5ac8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_dec5d5852b060024b87f5ac8-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_dec5d5852b060024b87f5ac8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_dec5d5852b060024b87f5ac8-0.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_dec5d5852b060024b87f5ac8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_dec5d5852b060024b87f5ac8-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_dec5d5852b060024b87f5ac8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_dec5d5852b060024b87f5ac8-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_dec5d5852b060024b87f5ac8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_dec5d5852b060024b87f5ac8-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.8921971252566734 #### count 487 #### university ##### size 4872 ##### gpa Percentile 72 ##### count Percentile 80 ##### median Count 141 ##### 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 | 9 | false | | 2.8–3.2 | 272 | false | | 3.2–3.6 | 1197 | false | | 3.6–4.0 | 3394 | true | #### departments ```json [ { "subject": "STAT", "comparison": { "size": 72, "gpaPercentile": 90, "countPercentile": 68, "medianCount": 246.5, "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": 8, "current": false }, { "range": "3.2–3.6", "count": 32, "current": false }, { "range": "3.6–4.0", "count": 32, "current": true } ] } } ] ``` ### terms #### 1164 ##### term 1164 ##### gpa 4 ##### count 12 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1184 ##### term 1184 ##### gpa 3.4456521739130435 ##### count 46 ##### university ###### size 1010 ###### gpa Percentile 44 ###### count Percentile 29 ###### 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 | 26 | false | | 2.8–3.2 | 210 | false | | 3.2–3.6 | 355 | true | | 3.6–4.0 | 418 | false | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 25, "gpaPercentile": 54, "countPercentile": 25, "medianCount": 70, "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": 6, "current": false }, { "range": "3.2–3.6", "count": 11, "current": true }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1194 ##### term 1194 ##### gpa 3.902439024390244 ##### count 41 ##### university ###### size 1040 ###### gpa Percentile 86 ###### count Percentile 21 ###### 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 | 23 | false | | 2.8–3.2 | 220 | false | | 3.2–3.6 | 342 | false | | 3.6–4.0 | 454 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 23, "gpaPercentile": 100, "countPercentile": 9, "medianCount": 79, "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": 6, "current": false }, { "range": "3.2–3.6", "count": 9, "current": false }, { "range": "3.6–4.0", "count": 7, "current": true } ] } } ] ``` #### 1202 ##### term 1202 ##### gpa 4 ##### count 73 ##### university ###### size 1102 ###### gpa Percentile 96 ###### count Percentile 53 ###### 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 | false | | 3.2–3.6 | 371 | false | | 3.6–4.0 | 498 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 30, "gpaPercentile": 97, "countPercentile": 38, "medianCount": 80.5, "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": 10, "current": false }, { "range": "3.2–3.6", "count": 11, "current": false }, { "range": "3.6–4.0", "count": 9, "current": true } ] } } ] ``` #### 1212 ##### term 1212 ##### gpa 4 ##### count 64 ##### university ###### size 1111 ###### gpa Percentile 96 ###### count Percentile 46 ###### 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 | false | | 3.2–3.6 | 337 | false | | 3.6–4.0 | 611 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 25, "gpaPercentile": 100, "countPercentile": 29, "medianCount": 100, "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": 7, "current": false }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 8, "current": true } ] } } ] ``` #### 1222 ##### term 1222 ##### gpa 4 ##### count 38 ##### university ###### size 1157 ###### gpa Percentile 97 ###### count Percentile 18 ###### 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 | false | | 3.2–3.6 | 351 | false | | 3.6–4.0 | 614 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 32, "gpaPercentile": 100, "countPercentile": 16, "medianCount": 55.5, "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": false }, { "range": "3.2–3.6", "count": 10, "current": false }, { "range": "3.6–4.0", "count": 13, "current": true } ] } } ] ``` #### 1232 ##### term 1232 ##### gpa 3.992063492063492 ##### count 63 ##### university ###### size 1216 ###### gpa Percentile 95 ###### count Percentile 48 ###### 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 | false | | 3.2–3.6 | 356 | false | | 3.6–4.0 | 670 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 32, "gpaPercentile": 97, "countPercentile": 55, "medianCount": 60.5, "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": 11, "current": false }, { "range": "3.2–3.6", "count": 13, "current": false }, { "range": "3.6–4.0", "count": 8, "current": true } ] } } ] ``` #### 1242 ##### term 1242 ##### gpa 3.8469387755102042 ##### count 49 ##### university ###### size 1295 ###### gpa Percentile 73 ###### count Percentile 37 ###### 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 | 2 | false | | 2.4–2.8 | 11 | false | | 2.8–3.2 | 162 | false | | 3.2–3.6 | 394 | false | | 3.6–4.0 | 726 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 34, "gpaPercentile": 82, "countPercentile": 36, "medianCount": 55, "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": 13, "current": false }, { "range": "3.6–4.0", "count": 13, "current": true } ] } } ] ``` #### 1244 ##### term 1244 ##### gpa 3.7333333333333334 ##### count 15 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1252 ##### term 1252 ##### gpa 4 ##### count 34 ##### university ###### size 1333 ###### gpa Percentile 96 ###### count Percentile 10 ###### 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 | false | | 3.2–3.6 | 431 | false | | 3.6–4.0 | 773 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 32, "gpaPercentile": 100, "countPercentile": 13, "medianCount": 70.5, "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": false }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 9, "current": true } ] } } ] ``` #### 1254 ##### term 1254 ##### gpa 3.730769230769231 ##### count 13 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1262 ##### term 1262 ##### gpa 3.7222222222222223 ##### count 18 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1264 ##### term 1264 ##### gpa 3.880952380952381 ##### count 21 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | ### benchmarks #### all ##### school ###### size 4872 ###### gpa 3.6941679785016865 ###### top Share 83.98418631524052 ###### count 141 ##### STAT ###### size 72 ###### gpa 3.5589488420926827 ###### top Share 76.47304249006892 ###### count 246.5 #### terms ##### 1164 ###### school ###### size 965 ###### gpa 3.46491230798535 ###### top Share 69.92376287143657 ###### count 68 ###### STAT ###### size 21 ###### gpa 3.317795716655057 ###### top Share 62.84642273068802 ###### count 69 ##### 1184 ###### school ###### size 1010 ###### gpa 3.47925290354517 ###### top Share 70.86270937115944 ###### count 68 ###### STAT ###### size 25 ###### gpa 3.460210558661105 ###### top Share 70.42953406269322 ###### count 70 ##### 1194 ###### school ###### size 1040 ###### gpa 3.4906527436719808 ###### top Share 71.74728845515045 ###### count 67 ###### STAT ###### size 23 ###### gpa 3.3818127863152334 ###### top Share 66.9295898310719 ###### count 79 ##### 1202 ###### school ###### size 1102 ###### gpa 3.5102605987403313 ###### top Share 72.78244569053733 ###### count 68 ###### STAT ###### size 30 ###### gpa 3.4022744829589433 ###### top Share 67.29048111947832 ###### count 80.5 ##### 1212 ###### school ###### size 1111 ###### gpa 3.5856416028074487 ###### top Share 77.58926748660845 ###### count 68 ###### STAT ###### size 25 ###### gpa 3.4555542540486095 ###### top Share 69.54152339778892 ###### count 100 ##### 1222 ###### school ###### size 1157 ###### gpa 3.563052311875811 ###### top Share 76.64869058732418 ###### count 64 ###### STAT ###### size 32 ###### gpa 3.4861059411832307 ###### top Share 71.46520654148341 ###### count 55.5 ##### 1232 ###### school ###### size 1216 ###### gpa 3.575457431972425 ###### top Share 77.33712216234007 ###### count 66 ###### STAT ###### size 32 ###### gpa 3.4024781451477413 ###### top Share 66.63145704464162 ###### count 60.5 ##### 1234 ###### school ###### size 1188 ###### gpa 3.5799441677552393 ###### top Share 77.18256448537606 ###### count 65 ###### STAT ###### size 25 ###### gpa 3.396227416481204 ###### top Share 66.8429997070879 ###### count 67 ##### 1242 ###### school ###### size 1295 ###### gpa 3.595302892737449 ###### top Share 78.36291889885307 ###### count 67 ###### STAT ###### size 34 ###### gpa 3.4558758327213903 ###### top Share 69.10154863162224 ###### count 55 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### STAT ###### size 29 ###### gpa 3.390846810323202 ###### top Share 64.2629736611174 ###### count 62 ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ###### STAT ###### size 32 ###### gpa 3.423918594183889 ###### top Share 68.17668754351217 ###### count 70.5 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### STAT ###### size 28 ###### gpa 3.4752654121860003 ###### top Share 68.35873780152826 ###### count 70 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### STAT ###### size 29 ###### gpa 3.415022952129974 ###### top Share 64.95385808199006 ###### count 81 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### STAT ###### size 26 ###### gpa 3.343399816676682 ###### top Share 63.23102425546245 ###### count 66 ## instructor Trends ```json [ { "uid": "instructor_ac940d98fd555bfd1c37966e", "name": "HYUNSEUNG KANG", "count": 408, "terms": [ { "term": "1184", "count": 46, "sections": 1, "gpa": 3.4456521739130435 }, { "term": "1194", "count": 41, "sections": 1, "gpa": 3.902439024390244 }, { "term": "1202", "count": 73, "sections": 1, "gpa": 4 }, { "term": "1212", "count": 64, "sections": 1, "gpa": 4 }, { "term": "1222", "count": 38, "sections": 1, "gpa": 4 }, { "term": "1232", "count": 63, "sections": 1, "gpa": 3.992063492063492 }, { "term": "1242", "count": 49, "sections": 1, "gpa": 3.8469387755102042 }, { "term": "1252", "count": 34, "sections": 1, "gpa": 4 } ] }, { "uid": "instructor_9cc75f9b84f6da363f0b5fb0", "name": "HANYING JIANG", "count": 101, "terms": [ { "term": "1222", "count": 38, "sections": 1, "gpa": 4 }, { "term": "1232", "count": 63, "sections": 1, "gpa": 3.992063492063492 } ] }, { "uid": "instructor_f239799e8b1d244fb8b0f240", "name": "SIXU LI", "count": 73, "terms": [ { "term": "1252", "count": 34, "sections": 1, "gpa": 4 }, { "term": "1262", "count": 18, "sections": 1, "gpa": 3.7222222222222223 }, { "term": "1264", "count": 21, "sections": 1, "gpa": 3.880952380952381 } ] }, { "uid": "instructor_bc7547c463578e6a6f5351b8", "name": "ZHIFENG CHEN", "count": 64, "terms": [ { "term": "1242", "count": 49, "sections": 1, "gpa": 3.8469387755102042 }, { "term": "1244", "count": 15, "sections": 1, "gpa": 3.7333333333333334 } ] }, { "uid": "instructor_71e12ad537764a7f7f348a74", "name": "SAMEER DESHPANDE", "count": 28, "terms": [ { "term": "1244", "count": 15, "sections": 1, "gpa": 3.7333333333333334 }, { "term": "1254", "count": 13, "sections": 1, "gpa": 3.730769230769231 } ] }, { "uid": "instructor_253cce0f28321f783c10482f", "name": "JESSI KEHE", "count": 21, "terms": [ { "term": "1264", "count": 21, "sections": 1, "gpa": 3.880952380952381 } ] }, { "uid": "instructor_4e7dcf69a8ea9529cddc6b67", "name": "CECILE ANE", "count": 18, "terms": [ { "term": "1262", "count": 18, "sections": 1, "gpa": 3.7222222222222223 } ] }, { "uid": "instructor_706ebccaed66febaf1bfdfb7", "name": "PAUL NGUYEN", "count": 13, "terms": [ { "term": "1254", "count": 13, "sections": 1, "gpa": 3.730769230769231 } ] }, { "uid": "instructor_5983f7a189c2f65b2819f132", "name": "BRIAN YANDELL", "count": 12, "terms": [ { "term": "1164", "count": 12, "sections": 1, "gpa": 4 } ] } ] ``` ## following None recorded.