# MARKETNG 450: Marketing Analytics | UW–Madison [View on UW Courses](https://uwcourses.com/courses/MARKETNG_450) ## 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 e339546071cd1bee40ce8884d738a7e5d99d1e6161edb9e5fa2e0bf2b23e5027 ### course id MARKETNG 450 ### course uid course\_833ea9e9edb43b825f960546 ### catalog version id 5ad7890b99dc99e4d39a654121e28b93bb90cddc602be0ebc9bd9e9565a27d2d ### course number 450 ### subjects * MARKETNG ### title MARKETING ANALYTICS ### description Impact of analytics on successful marketing decisions. Topics include marketing metrics, digital analytics, marketing response models, segmentation, product design, experimentation and big data. It is designed for students with some background in quantitative methods and an exposure to basic marketing research concepts. A combination of lectures, cases and hands-on model building focused on marketing analytics. ### requirements text Sophomore standing,MARKETNG 300, and310. Not open to graduate students ### credit offering ids None recorded. ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id cab2e84aef43ecae84552a10400e2495ed9ec273f93f9e988d428c0c56885a6e ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary MARKETING ANALYTICS covers the impact of analytics on marketing decisions, including metrics, digital analytics, and big data. ### llm topics * Marketing metrics and digital analytics * Marketing response models and segmentation * Product design and experimentation ### llm skills * Marketing analytics model building * Application of marketing metrics and digital analytics ### llm assumed background * Quantitative methods background * Basic marketing research concepts ### llm search phrases * marketing analytics * marketing metrics * digital analytics * marketing response models * segmentation * product design * experimentation * big data * quantitative methods * marketing research ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash 41c8f21b0d08d4e4374418975efe699e21232ba2b81b88cd385fb0afeb9a2f6b #### course id MARKETNG 450 #### current instructors None recorded. #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered false #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Recent recorded grades — Spring 2023: 3.42 GPA, 83.3% A/AB (n=6 letter grades); Spring 2025: 3.58 GPA, 83.3% A/AB (n=6 letter grades); Spring 2026: 3.61 GPA, 92.9% A/AB (n=14 letter grades). ```json { "citations": [ { "course_id": "MARKETNG 450", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "f13abba3-e431-3c41-8391-2a9187bce778", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "MARKETNG 450", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "f13abba3-e431-3c41-8391-2a9187bce778", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "MARKETNG 450", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "f13abba3-e431-3c41-8391-2a9187bce778", "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 None recorded. #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [ "n1", "n2", "n3", "n4" ], "condition": null, "course": null, "evidence": "Sophomore standing,MARKETNG 300, and310. Not open to graduate students", "id": "n0", "kind": "all" }, { "children": [], "condition": "Sophomore standing", "course": null, "evidence": "Sophomore standing", "id": "n1", "kind": "condition" }, { "children": [], "condition": null, "course": { "course_number": 300, "minimum_grade": null, "subjects": [ "MARKETNG" ], "timing": "prior" }, "evidence": "MARKETNG 300", "id": "n2", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 310, "minimum_grade": null, "subjects": [ "MARKETNG" ], "timing": "prior" }, "evidence": "and310", "id": "n3", "kind": "course" }, { "children": [], "condition": "Not open to graduate students", "course": null, "evidence": "Not open to graduate students", "id": "n4", "kind": "condition" } ] ``` #### notes * Unlinked course mention 'MARKETNG 300' and 'MARKETNG 310' are treated as course nodes based on linked\_courses. 'Sophomore standing' and 'Not open to graduate students' are condition leaves. #### root n0 #### status parsed ### instructors None recorded. ### offerings None recorded. ### sections None recorded. ### grade instructors ```json [ { "instructor_uid": "instructor_1d3e494a697132c88fac91ef", "source": "madgrades", "source_instructor_id": "4728495", "identity_basis": "source_id", "identity_status": "source_identified", "name": "MIN TIAN", "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": 3.5, "graded": 18, "counts": [ 6, 6, 6, 0, 0, 0, 0 ], "sections": 1 }, "instructor_url": "/instructors/MIN_TIAN" }, { "instructor_uid": "instructor_112e3a54d90f201c0d47a375", "source": "madgrades", "source_instructor_id": "3039911", "identity_basis": "source_id", "identity_status": "source_identified", "name": "NEERAJ ARORA", "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": 3.525, "graded": 785, "counts": [ 261, 323, 187, 11, 2, 0, 1 ], "sections": 87 }, "instructor_url": "/instructors/NEERAJ_ARORA--instructor_112e3a54d90f201c0d47a375" }, { "instructor_uid": "instructor_a74a00f460f90f4ebbc7efbb", "source": "madgrades", "source_instructor_id": "5539047", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SRINIVAS TUNUGUNTLA", "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": 3.724, "graded": 134, "counts": [ 81, 33, 19, 1, 0, 0, 0 ], "sections": 5 }, "instructor_url": "/instructors/SRINIVAS_TUNUGUNTLA--instructor_a74a00f460f90f4ebbc7efbb" }, { "instructor_uid": "instructor_dea0d74dc100adbde7b63aa3", "source": "madgrades", "source_instructor_id": "6353983", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ALEC ROCKWOOD", "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": 3.5, "graded": 88, "counts": [ 27, 34, 27, 0, 0, 0, 0 ], "sections": 3 }, "instructor_url": "/instructors/ALEC_ROCKWOOD--instructor_dea0d74dc100adbde7b63aa3" }, { "instructor_uid": "instructor_a769c80907de2fd894b3c13a", "source": "madgrades", "source_instructor_id": "4568672", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SARAH HOGUE", "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": 3.445, "graded": 91, "counts": [ 26, 31, 32, 2, 0, 0, 0 ], "sections": 4 }, "instructor_url": "/instructors/SARAH_HOGUE--instructor_a769c80907de2fd894b3c13a" }, { "instructor_uid": "instructor_9652d645cedbc0922eba529c", "source": "madgrades", "source_instructor_id": "4586069", "identity_basis": "source_id", "identity_status": "source_identified", "name": "CHENG HE", "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": 5, "quality": 5, "difficulty": 3.2, "quality_count": 5, "difficulty_count": 5, "profile_id": "rmp:2678730", "source_url": "https://www.ratemyprofessors.com/professor/2678730", "match_basis": "exact_name", "observed_at": "2026-09-07 16:49:03.105092+00:00", "courses": {}, "bayesian_quality": 3.9277486268372765, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.563, "graded": 311, "counts": [ 161, 68, 59, 12, 9, 1, 1 ], "sections": 18 }, "instructor_url": "/instructors/CHENG_HE--instructor_9652d645cedbc0922eba529c" }, { "instructor_uid": "instructor_a5cc8816df8361f3c07701a5", "source": "madgrades", "source_instructor_id": "6525718", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JAIDEEP KALSI", "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": 3.408, "graded": 49, "counts": [ 14, 16, 16, 2, 1, 0, 0 ], "sections": 4 }, "instructor_url": "/instructors/JAIDEEP_KALSI" }, { "instructor_uid": "instructor_1554d130dc69001305490f7c", "source": "madgrades", "source_instructor_id": "6687801", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JOSH CLARK", "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": 3.445, "graded": 64, "counts": [ 21, 27, 9, 6, 0, 0, 1 ], "sections": 3 }, "instructor_url": "/instructors/JOSH_CLARK" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1194", "term_name": "Spring 2019", "instructors": [ "MIN TIAN" ], "a": 6, "ab": 6, "b": 6, "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": [ "MARKETNG 450" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1204", "term_name": "Spring 2020", "instructors": [ "Neeraj Arora" ], "a": 7, "ab": 10, "b": 0, "bc": 0, "c": 1, "d": 0, "f": 0, "satisfactory": 7, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 25, "source_aliases": [ "MARKETNG 450" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1224", "term_name": "Spring 2022", "instructors": [ "Neeraj Arora", "SRINIVAS TUNUGUNTLA" ], "a": 2, "ab": 7, "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": 10, "source_aliases": [ "MARKETNG 450" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1234", "term_name": "Spring 2023", "instructors": [ "ALEC ROCKWOOD", "Neeraj Arora" ], "a": 0, "ab": 5, "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": 6, "source_aliases": [ "MARKETNG 450" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Neeraj Arora", "SARAH HOGUE" ], "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": [ "MARKETNG 450" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Cheng He", "JAIDEEP KALSI", "Neeraj Arora" ], "a": 2, "ab": 3, "b": 1, "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": 7, "source_aliases": [ "MARKETNG 450" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 450", "course_uid": "course_833ea9e9edb43b825f960546", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "JOSH CLARK", "Neeraj Arora" ], "a": 4, "ab": 9, "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": 14, "source_aliases": [ "MARKETNG 450" ] } ] ``` ### statistics #### gpa 3.556 #### graded 72 #### counts * 21 * 40 * 10 * 0 * 1 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_833ea9e9edb43b825f960546-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_833ea9e9edb43b825f960546-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_833ea9e9edb43b825f960546-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_833ea9e9edb43b825f960546-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_833ea9e9edb43b825f960546-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_833ea9e9edb43b825f960546-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.5555555555555554 #### count 72 #### university ##### size 3309 ##### gpa Percentile 26 ##### count Percentile 31 ##### median Count 124 ##### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 10 | false | | 2.8–3.2 | 181 | false | | 3.2–3.6 | 819 | true | | 3.6–4.0 | 2299 | false | #### departments ```json [ { "subject": "MARKETNG", "comparison": { "size": 40, "gpaPercentile": 33, "countPercentile": 23, "medianCount": 159.5, "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": 0, "current": false }, { "range": "3.2–3.6", "count": 15, "current": true }, { "range": "3.6–4.0", "count": 25, "current": false } ] } } ] ``` ### terms #### 1194 ##### term 1194 ##### gpa 3.5 ##### count 18 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | #### 1204 ##### term 1204 ##### gpa 3.611111111111111 ##### count 18 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | #### 1224 ##### term 1224 ##### gpa 3.55 ##### count 10 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | #### 1234 ##### term 1234 ##### gpa 3.4166666666666665 ##### count 6 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | #### 1254 ##### term 1254 ##### gpa 3.5833333333333335 ##### count 6 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | #### 1264 ##### term 1264 ##### gpa 3.607142857142857 ##### count 14 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | ### benchmarks #### all ##### school ###### size 3309 ###### gpa 3.69494530024415 ###### top Share 84.15308914222855 ###### count 124 ##### MARKETNG ###### size 40 ###### gpa 3.6441823543208685 ###### top Share 83.07165778702087 ###### count 159.5 #### terms ##### 1194 ###### school ###### size 1040 ###### gpa 3.4906527436719808 ###### top Share 71.74728845515045 ###### count 67 ###### MARKETNG ###### size 15 ###### gpa 3.5831559837896063 ###### top Share 78.75128949296631 ###### count 72 ##### 1204 ###### school ###### size 1012 ###### gpa 3.703747431523761 ###### top Share 84.59811226304916 ###### count 65.5 ###### MARKETNG ###### size 15 ###### gpa 3.711898594155838 ###### top Share 89.04767040292319 ###### count 47 ##### 1224 ###### school ###### size 1171 ###### gpa 3.5627882428500937 ###### top Share 76.37271640560496 ###### count 64 ###### MARKETNG ###### size 23 ###### gpa 3.640927073704417 ###### top Share 82.52296214470145 ###### count 58 ##### 1234 ###### school ###### size 1188 ###### gpa 3.5799441677552393 ###### top Share 77.18256448537606 ###### count 65 ###### MARKETNG ###### size 25 ###### gpa 3.6234775035319644 ###### top Share 80.59975420956242 ###### count 58 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### MARKETNG ###### size 23 ###### gpa 3.5744699156490247 ###### top Share 78.42184566175688 ###### count 57 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### MARKETNG ###### size 17 ###### gpa 3.481456315169987 ###### top Share 71.32646556786042 ###### count 54 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### MARKETNG ###### size 16 ###### gpa 3.483591884557984 ###### top Share 73.98101796980842 ###### count 52.5 ## instructor Trends ```json [ { "uid": "instructor_112e3a54d90f201c0d47a375", "name": "NEERAJ ARORA", "count": 54, "terms": [ { "term": "1204", "count": 18, "sections": 1, "gpa": 3.611111111111111 }, { "term": "1224", "count": 10, "sections": 1, "gpa": 3.55 }, { "term": "1234", "count": 6, "sections": 1, "gpa": 3.4166666666666665 }, { "term": "1254", "count": 6, "sections": 1, "gpa": 3.5833333333333335 }, { "term": "1264", "count": 14, "sections": 1, "gpa": 3.607142857142857 } ] }, { "uid": "instructor_1d3e494a697132c88fac91ef", "name": "MIN TIAN", "count": 18, "terms": [ { "term": "1194", "count": 18, "sections": 1, "gpa": 3.5 } ] }, { "uid": "instructor_1554d130dc69001305490f7c", "name": "JOSH CLARK", "count": 14, "terms": [ { "term": "1264", "count": 14, "sections": 1, "gpa": 3.607142857142857 } ] }, { "uid": "instructor_a74a00f460f90f4ebbc7efbb", "name": "SRINIVAS TUNUGUNTLA", "count": 10, "terms": [ { "term": "1224", "count": 10, "sections": 1, "gpa": 3.55 } ] }, { "uid": "instructor_a5cc8816df8361f3c07701a5", "name": "JAIDEEP KALSI", "count": 6, "terms": [ { "term": "1254", "count": 6, "sections": 2, "gpa": 3.5833333333333335 } ] }, { "uid": "instructor_dea0d74dc100adbde7b63aa3", "name": "ALEC ROCKWOOD", "count": 6, "terms": [ { "term": "1234", "count": 6, "sections": 1, "gpa": 3.4166666666666665 } ] } ] ``` ## following None recorded.