# GENBUS 317: Mathematical Foundations of Business Analytics | UW–Madison [View on UW Courses](https://uwcourses.com/courses/GENBUS_317) ## 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 3462f0ec072eab9068123c2da0ad01d496407afec7fe53ab790ac457660e5460 ### course id GENBUS 317 ### course uid course\_3f32a30c0076803c25219bbc ### catalog version id 39aa3bc9ee0897006e198890e53715493b67f75cb4bdcf5eac23c32b4dabfa38 ### course number 317 ### subjects * GENBUS ### title MATHEMATICAL FOUNDATIONS OF BUSINESS ANALYTICS ### description Statistical inference and analyses based on models will be introduced and applied in a business context using a calculus-based focus. Topics covered include point estimation, confidence intervals, hypothesis testing, regression models, and time series models. Various methods for fitting a model to data will be explored, and uncertainty about parameter estimates will be quantified so decision makers have information about the quality of the estimates. Regression and time series models are commonly used in business analytics applications and will be used to analyze business data and make inferences and predictions. ### requirements text MATH 331,STAT/​MATH  309, or431 ### credits min 3 ### credits max 3 ### credit offering ids * 1272:231:026584 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 77827e2328dca9ff2d063a3c2c3a38eab81a5dc381fd2bab2941dfa40a349b4e ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary GENBUS 317 teaches statistical inference and model-based analysis for business analytics, covering estimation, hypothesis testing, regression, and time series. ### llm topics * Point estimation and confidence intervals. * Hypothesis testing. * Regression models. * Time series models. ### llm skills * Statistical inference and model-based analysis. * Business data analysis and prediction using regression and time series. * Quantifying uncertainty in parameter estimates. ### llm assumed background * Probability theory and mathematical statistics fundamentals. ### llm search phrases * business analytics statistical inference * regression models business data * hypothesis testing business context * time series models business * calculus based statistics business ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash f0b16d4e3dd74b8a59c90beea5096ef402d75a1ec681638bcc63c71bc8a3c0c2 #### course id GENBUS 317 #### current instructors ```json [ { "instructor_uid": "instructor_3508804c3639fcfd0ab68610", "message": "No course-specific reviews available", "name": "Margie Rosenberg", "review_status": "no_course_reviews", "rmp_instructor_id": "rmp:2329429", "summary": [ { "citations": [ { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" } ], "text": "Recent recorded grades — Spring 2024: 3.42 GPA, 63.2% A/AB (n=19 letter grades); Fall 2024: 3.22 GPA, 62.1% A/AB (n=29 letter grades)." } ] } ] ``` #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered true #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Recent recorded grades — Spring 2025: 3.41 GPA, 59.4% A/AB (n=32 letter grades); Fall 2025: 3.41 GPA, 68.6% A/AB (n=35 letter grades); Spring 2026: 3.49 GPA, 75.7% A/AB (n=37 letter grades). ```json { "citations": [ { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history MARJORIE ROSENBERG is recorded teaching in Spring 2024, Fall 2024. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "GENBUS 317", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "source_record": { "entity_id": "1b1f682e-f741-3005-97f3-3929f7d14d30", "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": [ "n1", "n2", "n3" ], 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"course_3f32a30c0076803c25219bbc", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Margie Rosenberg" ], "a": 7, "ab": 5, "b": 5, "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": 19, "source_aliases": [ "GENBUS 317" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENBUS 317", "course_uid": "course_3f32a30c0076803c25219bbc", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Margie Rosenberg" ], "a": 9, "ab": 9, "b": 2, "bc": 4, "c": 5, "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": 29, "source_aliases": [ "GENBUS 317" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENBUS 317", "course_uid": "course_3f32a30c0076803c25219bbc", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Paul Johnson" ], "a": 11, "ab": 8, "b": 10, "bc": 2, "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": 32, "source_aliases": [ "GENBUS 317" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENBUS 317", "course_uid": "course_3f32a30c0076803c25219bbc", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Kirk Peter" ], "a": 13, "ab": 11, "b": 6, "bc": 2, "c": 3, "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": 35, "source_aliases": [ "GENBUS 317" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENBUS 317", "course_uid": "course_3f32a30c0076803c25219bbc", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Kirk Peter" ], "a": 14, "ab": 14, "b": 4, "bc": 4, "c": 1, "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": 38, "source_aliases": [ "GENBUS 317" ] } ] ``` ### statistics #### gpa 3.395 #### graded 152 #### counts * 54 * 47 * 27 * 13 * 11 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_3f32a30c0076803c25219bbc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_3f32a30c0076803c25219bbc-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_3f32a30c0076803c25219bbc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_3f32a30c0076803c25219bbc-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_3f32a30c0076803c25219bbc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_3f32a30c0076803c25219bbc-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_3f32a30c0076803c25219bbc-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_3f32a30c0076803c25219bbc-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.3947368421052633 #### count 152 #### university ##### size 3497 ##### gpa Percentile 15 ##### count Percentile 66 ##### median Count 92 ##### 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 | 13 | false | | 2.8–3.2 | 187 | false | | 3.2–3.6 | 894 | true | | 3.6–4.0 | 2403 | false | #### departments ```json [ { "subject": "GENBUS", "comparison": { "size": 45, "gpaPercentile": 14, "countPercentile": 36, "medianCount": 232, "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": 2, "current": false }, { "range": "3.2–3.6", "count": 8, "current": true }, { "range": "3.6–4.0", "count": 35, "current": false } ] } } ] ``` ### terms #### 1244 ##### term 1244 ##### gpa 3.4210526315789473 ##### count 19 ##### departments | subject | comparison | | ------- | ---------- | | GENBUS | | #### 1252 ##### term 1252 ##### gpa 3.2241379310344827 ##### count 29 ##### departments | subject | comparison | | ------- | ---------- | | GENBUS | | #### 1254 ##### term 1254 ##### gpa 3.40625 ##### count 32 ##### university ###### size 1289 ###### gpa Percentile 24 ###### count Percentile 5 ###### 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": "GENBUS", "comparison": { "size": 28, "gpaPercentile": 22, "countPercentile": 7, "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": 1, "current": false }, { "range": "3.2–3.6", "count": 11, "current": true }, { "range": "3.6–4.0", "count": 16, "current": false } ] } } ] ``` #### 1262 ##### term 1262 ##### gpa 3.414285714285714 ##### count 35 ##### university ###### size 1320 ###### gpa Percentile 23 ###### count Percentile 11 ###### 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": "GENBUS", "comparison": { "size": 27, "gpaPercentile": 19, "countPercentile": 4, "medianCount": 98, "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": 1, "current": false }, { "range": "3.2–3.6", "count": 9, "current": true }, { "range": "3.6–4.0", "count": 17, "current": false } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.4864864864864864 ##### count 37 ##### university ###### size 1283 ###### gpa Percentile 28 ###### count Percentile 13 ###### 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 | true | | 3.6–4.0 | 789 | false | ##### departments ```json [ { "subject": "GENBUS", "comparison": { "size": 30, "gpaPercentile": 17, "countPercentile": 24, "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": 0, "current": false }, { "range": "2.8–3.2", "count": 1, "current": false }, { "range": "3.2–3.6", "count": 7, "current": true }, { "range": "3.6–4.0", "count": 22, "current": false } ] } } ] ``` ### benchmarks #### all ##### school ###### size 3497 ###### gpa 3.6919469846564397 ###### top Share 83.92346882613002 ###### count 92 ##### GENBUS ###### size 45 ###### gpa 3.7055330319410857 ###### top Share 84.88254113316262 ###### count 232 #### terms ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### GENBUS ###### size 19 ###### gpa 3.534713725247456 ###### top Share 74.84471631838613 ###### count 100 ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ###### GENBUS ###### size 19 ###### gpa 3.6363102953835043 ###### top Share 81.30939457403292 ###### count 158 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### GENBUS ###### size 28 ###### gpa 3.642800867856554 ###### top Share 80.80715279553331 ###### count 83 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### GENBUS ###### size 27 ###### gpa 3.655019994289601 ###### top Share 82.47740840714685 ###### count 98 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### GENBUS ###### size 30 ###### gpa 3.6817668874579623 ###### top Share 83.39332566820664 ###### count 79 ## instructor Trends ```json [ { "uid": "instructor_1bc83c854b968d9486432407", "name": "KIRK PETER", "count": 72, "terms": [ { "term": "1262", "count": 35, "sections": 1, "gpa": 3.414285714285714 }, { "term": "1264", "count": 37, "sections": 1, "gpa": 3.4864864864864864 } ] }, { "uid": "instructor_853754eefd11575fc47740a1", "name": "MARJORIE ROSENBERG", "count": 48, "terms": [ { "term": "1244", "count": 19, "sections": 1, "gpa": 3.4210526315789473 }, { "term": "1252", "count": 29, "sections": 1, "gpa": 3.2241379310344827 } ] }, { "uid": "instructor_a543224f2b400e44d06c4237", "name": "PAUL JOHNSON", "count": 32, "terms": [ { "term": "1254", "count": 32, "sections": 1, "gpa": 3.40625 } ] } ] ``` ## following | code | title | | ---------------- | -------------------------------------------------------------- | | ACCTIS 640 | FOUNDATION IN ACCOUNTING ANALYTICS | | ACTSCI 640 | ACTUARIAL STATISTICS FOR RISK MODELING | | ACTSCI 652 | FUNDAMENTALS OF SHORT-TERM ACTUARIAL MODELING | | ECON/FINANCE 320 | INVESTMENT THEORY | | FINANCE 325 | CORPORATION FINANCE | | FINANCE 330 | DERIVATIVE SECURITIES | | GENBUS 308 | CLOUD ANALYTICS AND ARTIFICIAL INTELLIGENCE TOOLS FOR BUSINESS | | GENBUS 656 | FOUNDATIONS OF STATISTICAL LEARNING FOR BUSINESS ANALYTICS | | STAT 303 | R FOR STATISTICS I |