# COMPSCI/ECE 561: Probability and Information Theory in Machine Learning | UW–Madison [View on UW Courses](https://uwcourses.com/courses/COMPSCI_ECE_561) ## 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 58e5d5e6617968cbd60189cae88b1058b2f11bf878a09aa15bd6dee1df8a014f ### course id COMPSCI/ECE 561 ### course uid course\_6c482ec020432fe1bd6dc1fc ### catalog version id 8077732fbc1e1adc39422c816f3f5db79716ada785c7d05fcc63c61f60de4190 ### course number 561 ### subjects * COMPSCI * ECE ### title PROBABILITY AND INFORMATION THEORY IN MACHINE LEARNING ### description Probabilistic tools for machine learning and analysis of real-world datasets. Introductory topics include classification, regression, probability theory, decision theory and quantifying information with entropy, relative entropy and mutual information. Additional topics include naive Bayes, probabilistic graphical models, discriminant analysis, logistic regression, expectation maximization, source coding and variational inference. ### requirements text (MATH 320,340,341,375, orM E/​COMP SCI/​E C E  532or concur enroll) and (E C E 331,STAT/​MATH  309,431,STAT 311,324,424,MATH 531, or M E 424 prior to Fall 2026), grad/profsnl standing, or decl in Capstone Cert in Computer Sciences for Professionals ### credit offering ids None recorded. ### llm job id enrich-f516c4d3e82cfe326b4f5f54 ### llm output id 050fc7ba8de8e4716f07d21683f659a360eb2fb31e766ed1a2b36adb09640f08 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Covers probabilistic tools and information theory for machine learning, including classification, regression, and graphical models. ### llm topics * Probability theory, decision theory, and information measures. * Naive Bayes, graphical models, and variational inference. ### llm skills * Classification, regression, and decision theory. * Naive Bayes, probabilistic graphical models, and variational inference. ### llm assumed background * Linear algebra and differential equations, matrix methods, and probability/statistics fundamentals. * Matrix algebra, linear systems, and numerical methods for differential equations. * Probability theory, random variables, and statistical analysis. ### llm search phrases * probabilistic machine learning * information theory entropy * naive Bayes classification * probabilistic graphical models * variational inference * expectation maximization ### llm requirements status needs\_review ### llm student summary status valid ### llm experience status valid ### catalog variants None recorded. ### student summary #### context hash 2f4e7e300a22361d96378bafa054d9677f097b28f3d47f2968bc011973c9a554 #### course id COMPSCI/ECE 561 #### current instructors None recorded. #### difficulty workload Historical reviews of John Gubner: Three tricky exams determine 60% of the grade, creating a needlessly stressful environment. ```json { "citations": [ { "instructor_name": "John Gubner", "review_date": "2023-12-26 14:56:30 +0000 UTC", "review_id": "6da86aff22c530acdf8fd7e5", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1488414", "source_review_id": "UmF0aW5nLTM4Nzk0NzUx", "source_url": "https://www.ratemyprofessors.com/professor/1488414", "type": "review" } ] } ``` #### errors None recorded. #### historical context Historical reviews of John Gubner: John Gubner is highly knowledgeable and curves well, often resulting in high grades. However, his lectures are difficult to follow, assuming prior knowledge, and the course is stressful due to logistics and tricky exams. ```json { "citations": [ { "instructor_name": "John Gubner", "review_date": "2023-12-26 14:56:30 +0000 UTC", "review_id": "6da86aff22c530acdf8fd7e5", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1488414", "source_review_id": "UmF0aW5nLTM4Nzk0NzUx", "source_url": "https://www.ratemyprofessors.com/professor/1488414", "type": "review" } ] } ``` #### offered false #### profile hash e59ddc7389015d0035b68cd195c939d475bf72b959b29cf12eab59b454ccaef1 #### quick take Historical reviews of John Gubner: John Gubner's course is highly stressful due to logistics and difficult lectures, though he is knowledgeable and curves well. ```json { "citations": [ { "instructor_name": "John Gubner", "review_date": "2023-12-26 14:56:30 +0000 UTC", "review_id": "6da86aff22c530acdf8fd7e5", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1488414", "source_review_id": "UmF0aW5nLTM4Nzk0NzUx", "source_url": "https://www.ratemyprofessors.com/professor/1488414", "type": "review" } ] } ``` Recent recorded grades — Fall 2022: 3.62 GPA, 76.6% A/AB (n=47 letter grades); Fall 2023: 3.40 GPA, 61.7% A/AB (n=47 letter grades); Fall 2024: 3.96 GPA, 97.5% A/AB (n=40 letter grades). ```json { "citations": [ { "course_id": "COMPSCI/ECE 561", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "41017cd0-0e3a-3ea7-85e3-8581a8c5e68b", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "COMPSCI/ECE 561", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "41017cd0-0e3a-3ea7-85e3-8581a8c5e68b", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "COMPSCI/ECE 561", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "41017cd0-0e3a-3ea7-85e3-8581a8c5e68b", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1252", "type": "grade" } ] } ``` #### student experience Historical reviews of John Gubner: Lectures are hard to follow as if assuming prior knowledge, but the curve allows most students to get A or AB grades. ```json { "citations": [ { "instructor_name": "John Gubner", "review_date": "2023-12-26 14:56:30 +0000 UTC", "review_id": "6da86aff22c530acdf8fd7e5", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1488414", "source_review_id": "UmF0aW5nLTM4Nzk0NzUx", "source_url": "https://www.ratemyprofessors.com/professor/1488414", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history JOHN GUBNER is recorded teaching in Fall 2023. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "COMPSCI/ECE 561", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "41017cd0-0e3a-3ea7-85e3-8581a8c5e68b", "source_record": { "entity_id": "41017cd0-0e3a-3ea7-85e3-8581a8c5e68b", "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": [ "req_math_or_532", "req_ece_stat_math_or_me" ], "condition": null, "course": null, "evidence": "(MATH 320,340,341,375, orM E/COMP SCI/E C E 532or concur enroll) and (E C E 331,STAT/MATH 309,431,STAT 311,324,424,MATH 531, or M E 424 prior to Fall 2026)", "id": "req_root", "kind": "all" }, { "children": [ "req_math_320", "req_math_340", "req_math_341", "req_math_375", "req_math_532" ], "condition": 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"req_stat_math_309", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 431, "minimum_grade": null, "subjects": [ "MATH", "STAT" ], "timing": "prior" }, "evidence": "431", "id": "req_stat_math_431", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 311, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "STAT 311", "id": "req_stat_311", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 324, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "324", "id": "req_stat_324", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 424, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "424", "id": "req_stat_424", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 531, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, 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"difficulty": 4.75, "quality_count": 4, "difficulty_count": 4 }, "course_2ad9dc37c7e24009a8332e1e": { "review_count": 3, "quality": 3.67, "difficulty": 5, "quality_count": 3, "difficulty_count": 3 } }, "bayesian_quality": 2.9023207279782017, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.184, "graded": 1147, "counts": [ 348, 250, 265, 144, 104, 22, 14 ], "sections": 76 }, "instructor_url": "/instructors/JOHN_GUBNER--instructor_38edc69039c8c5387d9c7c31" }, { "instructor_uid": "instructor_a0635de9e0867a015d9ba90e", "source": "madgrades", "source_instructor_id": "669258", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ROBERT NOWAK", "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": 21, "quality": 2.9, "difficulty": 4.48, "quality_count": 21, "difficulty_count": 21, "profile_id": "rmp:329243", "source_url": "https://www.ratemyprofessors.com/professor/329243", "match_basis": "exact_name", "observed_at": "2026-09-07 16:09:32.056734+00:00", "courses": { "course_b588d52f82ec62f25a4f2ece": { "review_count": 2, "quality": 4.5, "difficulty": 4, "quality_count": 2, "difficulty_count": 2 }, "course_1c943aa88ab6f61c9fa4c558": { "review_count": 3, "quality": 1.33, "difficulty": 4, "quality_count": 3, "difficulty_count": 3 }, "course_a7ce5ee394c07ac642067916": { "review_count": 9, "quality": 2.44, "difficulty": 4.67, "quality_count": 9, "difficulty_count": 9 }, "course_e0dea279cb4bde9b3cec752e": { "review_count": 1, "quality": 5, "difficulty": 5, "quality_count": 1, "difficulty_count": 1 }, "course_a4ae993219c28eb4a4c5c7e2": { "review_count": 1, "quality": 3, "difficulty": 3, "quality_count": 1, "difficulty_count": 1 }, "course_368722b4e51915750b4c0050": { "review_count": 1, "quality": 1, "difficulty": 5, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.2705784309983392, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.497, "graded": 936, "counts": [ 446, 238, 148, 51, 37, 11, 5 ], "sections": 166 }, "instructor_url": "/instructors/ROBERT_NOWAK--instructor_a0635de9e0867a015d9ba90e" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE 561", "course_uid": "course_6c482ec020432fe1bd6dc1fc", "term_id": "1084", "term_name": "Spring 2008", "instructors": [ "JOSEPH BISOGNANO" ], "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": [ "COMPSCI/ECE 561" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE 561", "course_uid": "course_6c482ec020432fe1bd6dc1fc", "term_id": "1222", "term_name": "Fall 2021", "instructors": [ "MATTHEW MALLOY" ], "a": 36, "ab": 18, "b": 6, "bc": 1, "c": 1, "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": 62, "source_aliases": [ "COMPSCI/ECE 561" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE 561", "course_uid": "course_6c482ec020432fe1bd6dc1fc", "term_id": "1232", "term_name": "Fall 2022", "instructors": [ "KANG WOOK LEE" ], "a": 25, "ab": 11, "b": 8, "bc": 3, "c": 0, "d": 0, "f": 0, "satisfactory": 3, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 50, "source_aliases": [ "COMPSCI/ECE 561" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE 561", "course_uid": "course_6c482ec020432fe1bd6dc1fc", "term_id": "1242", "term_name": "Fall 2023", "instructors": [ "John Gubner" ], "a": 18, "ab": 11, "b": 13, "bc": 3, "c": 1, "d": 1, "f": 0, "satisfactory": 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/ECE 561" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "COMPSCI/ECE 561", "course_uid": "course_6c482ec020432fe1bd6dc1fc", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Robert Nowak" ], "a": 38, "ab": 1, "b": 1, "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": 40, "source_aliases": [ "COMPSCI/ECE 561" ] } ] ``` ### statistics #### gpa 3.663 #### graded 196 #### counts * 117 * 41 * 28 * 7 * 2 * 1 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_6c482ec020432fe1bd6dc1fc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_6c482ec020432fe1bd6dc1fc-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_6c482ec020432fe1bd6dc1fc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_6c482ec020432fe1bd6dc1fc-0.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_6c482ec020432fe1bd6dc1fc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_6c482ec020432fe1bd6dc1fc-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_6c482ec020432fe1bd6dc1fc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_6c482ec020432fe1bd6dc1fc-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.663265306122449 #### count 196 #### university ##### size 2965 ##### gpa Percentile 45 ##### count Percentile 72 ##### median Count 101 ##### 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 | 15 | false | | 2.8–3.2 | 264 | false | | 3.2–3.6 | 827 | false | | 3.6–4.0 | 1858 | true | #### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 81, "gpaPercentile": 49, "countPercentile": 50, "medianCount": 196, "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": 14, "current": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 44, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 73, "gpaPercentile": 54, "countPercentile": 53, "medianCount": 154, "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": 28, "current": false }, { "range": "3.6–4.0", "count": 37, "current": true } ] } } ] ``` ### terms #### 1222 ##### term 1222 ##### gpa 3.7016129032258065 ##### count 62 ##### university ###### size 1157 ###### gpa Percentile 58 ###### count Percentile 48 ###### 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": "COMPSCI", "comparison": { "size": 46, "gpaPercentile": 73, "countPercentile": 29, "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": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 14, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 41, "gpaPercentile": 68, "countPercentile": 38, "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": 7, "current": false }, { "range": "3.2–3.6", "count": 18, "current": false }, { "range": "3.6–4.0", "count": 16, "current": true } ] } } ] ``` #### 1232 ##### term 1232 ##### gpa 3.617021276595745 ##### count 47 ##### university ###### size 1216 ###### gpa Percentile 47 ###### count Percentile 32 ###### 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": "COMPSCI", "comparison": { "size": 50, "gpaPercentile": 61, "countPercentile": 20, "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": false }, { "range": "3.2–3.6", "count": 19, "current": false }, { "range": "3.6–4.0", "count": 22, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 44, "gpaPercentile": 63, "countPercentile": 30, "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": 1, "current": false }, { "range": "2.8–3.2", "count": 10, "current": false }, { "range": "3.2–3.6", "count": 16, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } } ] ``` #### 1242 ##### term 1242 ##### gpa 3.404255319148936 ##### count 47 ##### university ###### size 1295 ###### gpa Percentile 27 ###### count Percentile 33 ###### 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 | true | | 3.6–4.0 | 726 | false | ##### departments ```json [ { "subject": "COMPSCI", "comparison": { "size": 52, "gpaPercentile": 39, "countPercentile": 25, "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": 1, "current": false }, { "range": "2.8–3.2", "count": 9, "current": false }, { "range": "3.2–3.6", "count": 20, "current": true }, { "range": "3.6–4.0", "count": 22, "current": false } ] } }, { "subject": "ECE", "comparison": { "size": 41, "gpaPercentile": 48, "countPercentile": 18, "medianCount": 83, "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": 18, "current": true }, { "range": "3.6–4.0", "count": 15, "current": false } ] } } ] ``` #### 1252 ##### term 1252 ##### gpa 3.9625 ##### count 40 ##### university ###### size 1333 ###### gpa Percentile 91 ###### count Percentile 21 ###### 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": "COMPSCI", "comparison": { "size": 54, "gpaPercentile": 91, "countPercentile": 19, "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": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 22, "current": true } ] } }, { "subject": "ECE", "comparison": { "size": 44, "gpaPercentile": 93, "countPercentile": 21, "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": 4, "current": false }, { "range": "3.2–3.6", "count": 23, "current": false }, { "range": "3.6–4.0", "count": 17, "current": true } ] } } ] ``` ### benchmarks #### all ##### school ###### size 2965 ###### gpa 3.6472755664915426 ###### top Share 81.2347737761883 ###### count 101 ##### COMPSCI ###### size 81 ###### gpa 3.584864112658546 ###### top Share 78.46476416862889 ###### count 196 ##### ECE ###### size 73 ###### gpa 3.554486706757168 ###### top Share 75.37871558427739 ###### count 154 #### terms ##### 1084 ###### school ###### size 720 ###### gpa 3.3670742938849725 ###### top Share 63.42064564712246 ###### count 70 ###### COMPSCI ###### size 14 ###### gpa 3.144553029581605 ###### top Share 50.3940565180559 ###### count 59 ###### ECE ###### size 16 ###### gpa 3.0875185917763455 ###### top Share 46.018020594418786 ###### count 47.5 ##### 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 ###### ECE ###### size 41 ###### gpa 3.502469130958549 ###### top Share 72.06914460291064 ###### count 70 ##### 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 ###### ECE ###### size 44 ###### gpa 3.4583903966894223 ###### top Share 70.01102622146537 ###### count 70 ##### 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 ###### ECE ###### size 41 ###### gpa 3.4916867437115484 ###### top Share 71.95296745580877 ###### count 83 ##### 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 ###### ECE ###### size 44 ###### gpa 3.5595929340853747 ###### top Share 76.26079811550397 ###### count 74 ## instructor Trends ```json [ { "uid": "instructor_f7c312e4d64fa1483275eb3f", "name": "MATTHEW MALLOY", "count": 62, "terms": [ { "term": "1222", "count": 62, "sections": 2, "gpa": 3.7016129032258065 } ] }, { "uid": "instructor_38edc69039c8c5387d9c7c31", "name": "JOHN GUBNER", "count": 47, "terms": [ { "term": "1242", "count": 47, "sections": 1, "gpa": 3.404255319148936 } ] }, { "uid": "instructor_c7da0e4affd180820e6970b5", "name": "KANG WOOK LEE", "count": 47, "terms": [ { "term": "1232", "count": 47, "sections": 1, "gpa": 3.617021276595745 } ] }, { "uid": "instructor_a0635de9e0867a015d9ba90e", "name": "ROBERT NOWAK", "count": 40, "terms": [ { "term": "1252", "count": 40, "sections": 1, "gpa": 3.9625 } ] } ] ``` ## following None recorded.