# MARKETNG 745: Digital Marketing Analytics | UW–Madison [View on UW Courses](https://uwcourses.com/courses/MARKETNG_745) ## 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 19efc93ae8de6e245ceeff82bb6b1a73f89b3142703d7ec8e38391011c459962 ### course id MARKETNG 745 ### course uid course\_4833d1a782cc592a64f85b44 ### catalog version id 4237f7350a32740751428172d844a5ae32bd94a3aa2428417e4ddb9010b29a0c ### course number 745 ### subjects * MARKETNG ### title DIGITAL MARKETING ANALYTICS ### description Introduces business analytic techniques applied in the context of digital marketing. Includes approaches to design, run, evaluate, and improve online marketing tactics in order to meet specific business objectives such as customer acquisition. Covers digital analytics methods and execution of marketing tactics with data-driven techniques. Emphasizes the implementation of analytic skills on practical problems. ### requirements text Graduate/professional standing ### credit offering ids None recorded. ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id cd9aecaa0de6148b4b4e1dd93e2512cfeadb5c9050d9cf9962999b5daf98e3b5 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary MARKETNG 745 introduces business analytic techniques for digital marketing, focusing on data-driven tactics for customer acquisition. ### llm topics * Digital marketing * Business analytic techniques * Online marketing tactics * Digital analytics methods * Customer acquisition ### llm skills * Design, run, evaluate, and improve online marketing tactics * Execute marketing tactics using digital analytics and data-driven techniques * Implement analytic skills on practical business problems ### llm assumed background None recorded. ### llm search phrases * digital marketing analytics * business analytic techniques * online marketing tactics * data-driven marketing * customer acquisition analytics ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash f861d67c9ff3f1c155ea7796ed0d0e36ba93a6c587f8a6b59a0ce11024fc5dd0 #### course id MARKETNG 745 #### 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 2024: 3.54 GPA, 69.2% A/AB (n=39 letter grades); Spring 2025: 3.37 GPA, 55.9% A/AB (n=34 letter grades); Spring 2026: 3.73 GPA, 81.8% A/AB (n=11 letter grades). ```json { "citations": [ { "course_id": "MARKETNG 745", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "905a83f5-3eea-3131-b3b1-98088236a516", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "MARKETNG 745", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "905a83f5-3eea-3131-b3b1-98088236a516", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "MARKETNG 745", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "905a83f5-3eea-3131-b3b1-98088236a516", "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": [], "condition": "Graduate/professional standing", "course": null, "evidence": "Graduate/professional standing", "id": "n0", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors None recorded. ### offerings None recorded. ### sections None recorded. ### grade instructors ```json [ { "instructor_uid": "instructor_8a453cb0b6b28bc4169587e5", "source": "madgrades", "source_instructor_id": "5329849", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ZHI HUANG", "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": 3.534, "graded": 191, "counts": [ 75, 67, 38, 9, 2, 0, 0 ], "sections": 8 }, "instructor_url": "/instructors/ZHI_HUANG" }, { "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_0caeeed03e5c3526ea11da5e", "source": "madgrades", "source_instructor_id": "6460808", "identity_basis": "source_id", "identity_status": "source_identified", "name": "XINGJIAN YOU", "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": 3.534, "graded": 525, "counts": [ 188, 211, 107, 16, 2, 0, 1 ], "sections": 16 }, "instructor_url": "/instructors/XINGJIAN_YOU" }, { "instructor_uid": "instructor_c6976f46a636bfc319006d4b", "source": "madgrades", "source_instructor_id": "6451948", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SHOURYA MAHESHWARI", "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": 3.587, "graded": 80, "counts": [ 43, 15, 17, 3, 2, 0, 0 ], "sections": 3 }, "instructor_url": "/instructors/SHOURYA_MAHESHWARI--instructor_c6976f46a636bfc319006d4b" }, { "instructor_uid": "instructor_1c241ab83c8bca8831d4c79a", "source": "madgrades", "source_instructor_id": "6372756", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JUNGEUN LIM", "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": 3.692, "graded": 650, "counts": [ 341, 236, 60, 8, 5, 0, 0 ], "sections": 18 }, "instructor_url": "/instructors/JUNGEUN_LIM" }, { "instructor_uid": "instructor_20c6ade525a903ffc3c550fb", "source": "madgrades", "source_instructor_id": "6615983", "identity_basis": "source_id", "identity_status": "source_identified", "name": "WENDY 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": 3.625, "graded": 224, "counts": [ 117, 71, 25, 3, 5, 3, 0 ], "sections": 10 }, "instructor_url": "/instructors/WENDY_JIANG" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 745", "course_uid": "course_4833d1a782cc592a64f85b44", "term_id": "1224", "term_name": "Spring 2022", "instructors": [ "Cheng He", "ZHI HUANG" ], "a": 19, "ab": 4, "b": 2, "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": 2, "other": 0, "total": 29, "source_aliases": [ "MARKETNG 745" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 745", "course_uid": "course_4833d1a782cc592a64f85b44", "term_id": "1234", "term_name": "Spring 2023", "instructors": [ "Cheng He", "XINGJIAN YOU" ], "a": 19, "ab": 13, "b": 9, "bc": 2, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 1, "other": 0, "total": 44, "source_aliases": [ "MARKETNG 745" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 745", "course_uid": "course_4833d1a782cc592a64f85b44", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Cheng He", "SHOURYA MAHESHWARI" ], "a": 19, "ab": 8, "b": 9, "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": 39, "source_aliases": [ "MARKETNG 745" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 745", "course_uid": "course_4833d1a782cc592a64f85b44", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Cheng He", "JUNGEUN LIM" ], "a": 10, "ab": 9, "b": 12, "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": 34, "source_aliases": [ "MARKETNG 745" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "MARKETNG 745", "course_uid": "course_4833d1a782cc592a64f85b44", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Cheng He", "WENDY JIANG" ], "a": 7, "ab": 2, "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": 11, "source_aliases": [ "MARKETNG 745" ] } ] ``` ### statistics #### gpa 3.555 #### graded 154 #### counts * 74 * 36 * 34 * 7 * 3 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_4833d1a782cc592a64f85b44-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_4833d1a782cc592a64f85b44-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_4833d1a782cc592a64f85b44-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_4833d1a782cc592a64f85b44-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_4833d1a782cc592a64f85b44-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_4833d1a782cc592a64f85b44-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.5551948051948052 #### count 154 #### university ##### size 2947 ##### gpa Percentile 28 ##### count Percentile 61 ##### median Count 113 ##### 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 | 11 | false | | 2.8–3.2 | 200 | false | | 3.2–3.6 | 728 | true | | 3.6–4.0 | 2007 | false | #### departments ```json [ { "subject": "MARKETNG", "comparison": { "size": 38, "gpaPercentile": 32, "countPercentile": 54, "medianCount": 144.5, "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": 1, "current": false }, { "range": "3.2–3.6", "count": 15, "current": true }, { "range": "3.6–4.0", "count": 22, "current": false } ] } } ] ``` ### terms #### 1224 ##### term 1224 ##### gpa 3.7222222222222223 ##### count 27 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | #### 1234 ##### term 1234 ##### gpa 3.5697674418604652 ##### count 43 ##### university ###### size 1188 ###### gpa Percentile 42 ###### count Percentile 27 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 3 | false | | 2.4–2.8 | 17 | false | | 2.8–3.2 | 144 | false | | 3.2–3.6 | 374 | true | | 3.6–4.0 | 650 | false | ##### departments ```json [ { "subject": "MARKETNG", "comparison": { "size": 25, "gpaPercentile": 38, "countPercentile": 29, "medianCount": 58, "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": 11, "current": true }, { "range": "3.6–4.0", "count": 14, "current": false } ] } } ] ``` #### 1244 ##### term 1244 ##### gpa 3.5384615384615383 ##### count 39 ##### university ###### size 1241 ###### gpa Percentile 37 ###### count Percentile 20 ###### median Count 65 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 2 | false | | 2.4–2.8 | 9 | false | | 2.8–3.2 | 151 | false | | 3.2–3.6 | 373 | true | | 3.6–4.0 | 706 | false | ##### departments ```json [ { "subject": "MARKETNG", "comparison": { "size": 23, "gpaPercentile": 36, "countPercentile": 23, "medianCount": 57, "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": 12, "current": true }, { "range": "3.6–4.0", "count": 10, "current": false } ] } } ] ``` #### 1254 ##### term 1254 ##### gpa 3.3676470588235294 ##### count 34 ##### university ###### size 1289 ###### gpa Percentile 21 ###### count Percentile 8 ###### 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": "MARKETNG", "comparison": { "size": 17, "gpaPercentile": 31, "countPercentile": 6, "medianCount": 54, "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": 9, "current": true }, { "range": "3.6–4.0", "count": 6, "current": false } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.727272727272727 ##### count 11 ##### departments | subject | comparison | | -------- | ---------- | | MARKETNG | | ### benchmarks #### all ##### school ###### size 2947 ###### gpa 3.684503227431485 ###### top Share 83.48969667841149 ###### count 113 ##### MARKETNG ###### size 38 ###### gpa 3.6204886794836764 ###### top Share 81.83787794444454 ###### count 144.5 #### terms ##### 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_9652d645cedbc0922eba529c", "name": "CHENG HE", "count": 154, "terms": [ { "term": "1224", "count": 27, "sections": 2, "gpa": 3.7222222222222223 }, { "term": "1234", "count": 43, "sections": 1, "gpa": 3.5697674418604652 }, { "term": "1244", "count": 39, "sections": 1, "gpa": 3.5384615384615383 }, { "term": "1254", "count": 34, "sections": 1, "gpa": 3.3676470588235294 }, { "term": "1264", "count": 11, "sections": 1, "gpa": 3.727272727272727 } ] }, { "uid": "instructor_0caeeed03e5c3526ea11da5e", "name": "XINGJIAN YOU", "count": 43, "terms": [ { "term": "1234", "count": 43, "sections": 1, "gpa": 3.5697674418604652 } ] }, { "uid": "instructor_c6976f46a636bfc319006d4b", "name": "SHOURYA MAHESHWARI", "count": 39, "terms": [ { "term": "1244", "count": 39, "sections": 1, "gpa": 3.5384615384615383 } ] }, { "uid": "instructor_1c241ab83c8bca8831d4c79a", "name": "JUNGEUN LIM", "count": 34, "terms": [ { "term": "1254", "count": 34, "sections": 1, "gpa": 3.3676470588235294 } ] }, { "uid": "instructor_8a453cb0b6b28bc4169587e5", "name": "ZHI HUANG", "count": 27, "terms": [ { "term": "1224", "count": 27, "sections": 2, "gpa": 3.7222222222222223 } ] }, { "uid": "instructor_20c6ade525a903ffc3c550fb", "name": "WENDY JIANG", "count": 11, "terms": [ { "term": "1264", "count": 11, "sections": 1, "gpa": 3.727272727272727 } ] } ] ``` ## following None recorded.