# CNSRSCI 301: Consumer Analytics | UW–Madison [View on UW Courses](https://uwcourses.com/courses/CNSRSCI_301) ## Dataset ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ### repository twangodev/uwcourses ### schema version 6 ### importer version 7 ### projection id 94468b7d4154126ca413937bb4738a6d21e0c2277f6fa397a6078ad80a32384f ### observed at 2026-09-07T15:55:43.033547+00:00 ### built at 2026-09-10T23:19:01.870283+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 d445dc4b104d9b9c8a225292da15ed0ffbb5c7bcdc61c4f1c2cfb34c0df93e6c ### course id CNSRSCI 301 ### course uid course\_e420cb4ad0fb5cdf16dee294 ### catalog version id d13491b8e0a868ac809fda760e2a7dd16783b5d33274934ef5684f3d4306e344 ### course number 301 ### subjects * CNSRSCI ### title CONSUMER ANALYTICS ### description Leverage data analysis to drive consumer business decisions via the telling of a compelling, evidence-based story. Structured to 1) provide you with a core process by which data analysis can produce effective business actions, 2) build your analytical abilities to execute the process and 3) establish a method by which analytical results can be transformed into effective stories. The process and methods studied will have application across a broad range of careers. ### requirements text CNSR SCI 201 ### credits min 3 ### credits max 3 ### credit offering ids * 1272:271:024473 ### llm job id enrich-f516c4d3e82cfe326b4f5f54 ### llm output id e4355db7636ef08f4684d08452e605c0d4501e494e63d2b9ff11ab5548109598 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Consumer Analytics teaches leveraging data analysis to drive business decisions through evidence-based storytelling. ### llm topics * Data analysis process for business actions * Transforming analytical results into stories ### llm skills * Leverage data analysis for business decisions * Tell compelling evidence-based stories * Execute data analysis processes * Transform analytical results into effective stories ### llm assumed background * Basic quantitative data analysis, descriptive and inferential statistics ### llm search phrases * consumer analytics data story * data analysis business decisions * consumer insights statistics * evidence-based business storytelling ### llm requirements status valid ### llm student summary status valid ### llm experience status valid ### catalog variants None recorded. ### student summary #### context hash 57e1d0996060cc2edb166831ffbc941e8313631cfc682f75c44457ee61e880ad #### course id CNSRSCI 301 #### current instructors ```json [ { "instructor_uid": "instructor_df7ca51acf159f69bce85581", "message": "No course-specific reviews available", "name": "Megan Bea", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [ { "citations": [ { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" } ], "text": "Recent recorded grades — Fall 2022: 3.41 GPA, 79.5% A/AB (n=44 letter grades); Spring 2023: 3.55 GPA, 81.5% A/AB (n=54 letter grades); Spring 2024: 3.15 GPA, 65.2% A/AB (n=23 letter grades). Includes jointly taught sections." } ] }, { "instructor_uid": "instructor_daeda993c969642ae5ee6b88", "message": "No course-specific reviews available", "name": "Wanting Jiang", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [] } ] ``` #### difficulty workload Exams are hard, but students learn a lot from them according to historical reviews of Yiwei Zhang. ```json { "citations": [ { "instructor_name": "Yiwei Zhang", "review_date": "2025-02-10 19:42:54 +0000 UTC", "review_id": "6c76fd05364795e843fc11a1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2556649", "source_review_id": "UmF0aW5nLTQwNjU3NjU4", "source_url": "https://www.ratemyprofessors.com/professor/2556649", "type": "review" } ] } ``` #### errors None recorded. #### historical context Historical reviews for Yiwei Zhang praise her for making material easier to understand and providing extensive resources like videos and PowerPoint slides. Reviewers also note that her exams are hard but effective for learning. ```json { "citations": [ { "instructor_name": "Yiwei Zhang", "review_date": "2019-12-16 20:30:18 +0000 UTC", "review_id": "b4975da450d888141dfc3136", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2556649", "source_review_id": "UmF0aW5nLTMyNjc5OTU5", "source_url": "https://www.ratemyprofessors.com/professor/2556649", "type": "review" }, { "instructor_name": "Yiwei Zhang", "review_date": "2025-02-10 19:42:54 +0000 UTC", "review_id": "6c76fd05364795e843fc11a1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2556649", "source_review_id": "UmF0aW5nLTQwNjU3NjU4", "source_url": "https://www.ratemyprofessors.com/professor/2556649", "type": "review" } ] } ``` #### offered true #### profile hash e59ddc7389015d0035b68cd195c939d475bf72b959b29cf12eab59b454ccaef1 #### quick take Historical reviews of Yiwei Zhang: Yiwei Zhang teaches statistics effectively, making the class great for analytics enthusiasts despite hard exams and early 8 am sections. ```json { "citations": [ { "instructor_name": "Yiwei Zhang", "review_date": "2025-02-10 19:42:54 +0000 UTC", "review_id": "6c76fd05364795e843fc11a1", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2556649", "source_review_id": "UmF0aW5nLTQwNjU3NjU4", "source_url": "https://www.ratemyprofessors.com/professor/2556649", "type": "review" } ] } ``` Recent recorded grades — Spring 2025: 3.42 GPA, 67.2% A/AB (n=61 letter grades); Fall 2025: 3.47 GPA, 68.6% A/AB (n=70 letter grades); Spring 2026: 3.16 GPA, 59.2% A/AB (n=49 letter grades). ```json { "citations": [ { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience Historical reviews of Yiwei Zhang: Yiwei Zhang makes material easier to understand and provides extensive outside resources like videos and powerpoints, with constructive feedback on projects. ```json { "citations": [ { "instructor_name": "Yiwei Zhang", "review_date": "2019-12-16 20:30:18 +0000 UTC", "review_id": "b4975da450d888141dfc3136", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:2556649", "source_review_id": "UmF0aW5nLTMyNjc5OTU5", "source_url": "https://www.ratemyprofessors.com/professor/2556649", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history MEGAN BEA is recorded teaching in Spring 2020, Spring 2022, Fall 2022, Spring 2023, Spring 2024. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1204", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1204", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1224", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1234", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1244", "type": "grade" } ] } ``` YIWEI ZHANG is recorded teaching in Fall 2019, Fall 2020, Fall 2021, Fall 2023, Fall 2024, Spring 2025, Fall 2025, Spring 2026. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1202", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1202", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 2, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 102, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "CNSRSCI 301", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "source_record": { "entity_id": "3e771c83-1958-3674-8f8b-909ed8f1d1d4", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [], "condition": null, "course": { "course_number": 201, "minimum_grade": null, "subjects": [ "CNSRSCI" ], "timing": "prior" }, "evidence": "CNSR SCI 201", "id": "n0", "kind": "course" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors | instructor\_uid | source | source\_instructor\_id | identity\_basis | identity\_status | name | email | first\_observed\_at | last\_observed\_at | instructor\_url | | ------------------------------------ | ---------- | ---------------------- | --------------- | ------------------ | ------------- | ------------------ | -------------------------------- | -------------------------------- | --------------------------- | | instructor\_df7ca51acf159f69bce85581 | enrollment | mbea | netid | source\_identified | Megan Bea | MBEA\@WISC.EDU | 2026-09-07 15:55:43.033547+00:00 | 2026-09-07 15:55:43.033547+00:00 | /instructors/MEGAN\_BEA | | instructor\_daeda993c969642ae5ee6b88 | enrollment | wjiang96 | netid | source\_identified | Wanting Jiang | WJIANG96\@WISC.EDU | 2026-09-07 15:55:43.033547+00:00 | 2026-09-07 15:55:43.033547+00:00 | /instructors/WANTING\_JIANG | ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:271:024473", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1272", "source_course_id": "024473", "source_subject_id": "271", "title": "Consumer Analytics", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:34672", "term_id": "1272", "source_section_id": "34672", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 48, "enrolled": 48, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" } ] ``` ### grade instructors ```json [ { "instructor_uid": "instructor_02b717bc90cf7826f7a66079", "source": "madgrades", "source_instructor_id": "4874607", "identity_basis": "source_id", "identity_status": "source_identified", "name": "TAYLER 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", "grade_statistics": { "gpa": 3.527, "graded": 311, "counts": [ 113, 133, 38, 23, 4, 0, 0 ], "sections": 6 }, "instructor_url": "/instructors/TAYLER_NOWAK" }, { "instructor_uid": "instructor_0528d1d144df225fe51d3519", "source": "madgrades", "source_instructor_id": "4697293", "identity_basis": "source_id", "identity_status": "source_identified", "name": "DEE WARMATH", "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": 11, "quality": 4, "difficulty": 2.55, "quality_count": 11, "difficulty_count": 11, "profile_id": "rmp:1821069", "source_url": "https://www.ratemyprofessors.com/professor/1821069", "match_basis": "exact_name", "observed_at": "2026-09-07 16:44:01.490798+00:00", "courses": {}, "bayesian_quality": 3.7804424409978035, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.418, "graded": 631, "counts": [ 165, 267, 146, 42, 9, 1, 1 ], "sections": 26 }, "instructor_url": "/instructors/DEE_WARMATH" }, { "instructor_uid": "instructor_acf0bf2387eac107d4ce4749", "source": "madgrades", "source_instructor_id": "3126020", "identity_basis": "source_id", "identity_status": "source_identified", "name": "KRISTIN BRANCH", "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": 27, "quality": 3.3, "difficulty": 3.3, "quality_count": 27, "difficulty_count": 27, "profile_id": "rmp:3063248", "source_url": "https://www.ratemyprofessors.com/professor/3063248", "match_basis": "exact_name", "observed_at": "2026-09-07 16:25:31.593434+00:00", "courses": { "course_b5acb9d443607a19cb772ba8": { "review_count": 27, "quality": 3.3, "difficulty": 3.3, "quality_count": 27, "difficulty_count": 27 } }, "bayesian_quality": 3.4530577802325935, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.464, "graded": 3379, "counts": [ 1461, 1010, 460, 294, 83, 46, 25 ], "sections": 62 }, "instructor_url": "/instructors/KRISTIN_BRANCH--instructor_acf0bf2387eac107d4ce4749" }, { "instructor_uid": "instructor_dcc1a85d04f35e1240ed8a6d", "source": "madgrades", "source_instructor_id": "540869", "identity_basis": "source_id", "identity_status": "source_identified", "name": "PATRICIA SIGLER", "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": 3.745, "graded": 2058, "counts": [ 1424, 396, 131, 64, 31, 11, 1 ], "sections": 34 }, "instructor_url": "/instructors/PATRICIA_SIGLER--instructor_dcc1a85d04f35e1240ed8a6d" }, { "instructor_uid": "instructor_4214af0bd920d2865ac013b5", "source": "madgrades", "source_instructor_id": "3908511", "identity_basis": "source_id", "identity_status": "source_identified", "name": "YIWEI ZHANG", "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": 4, "quality": 4.25, "difficulty": 3.5, "quality_count": 4, "difficulty_count": 4, "profile_id": "rmp:2556649", "source_url": "https://www.ratemyprofessors.com/professor/2556649", "match_basis": "exact_name", "observed_at": "2026-09-07 16:32:31.825347+00:00", "courses": { "course_e420cb4ad0fb5cdf16dee294": { "review_count": 2, "quality": 5, "difficulty": 4, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.7580714862888294, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.396, "graded": 499, "counts": [ 199, 138, 85, 47, 17, 9, 4 ], "sections": 30 }, "instructor_url": "/instructors/YIWEI_ZHANG--instructor_4214af0bd920d2865ac013b5" }, { "instructor_uid": "instructor_838e6af1a533c6ccd2cd049c", "source": "madgrades", "source_instructor_id": "6236760", "identity_basis": "source_id", "identity_status": "source_identified", "name": "MEGAN BEA", "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": 3.596, "graded": 528, "counts": [ 265, 175, 55, 16, 8, 5, 4 ], "sections": 31 }, "instructor_url": "/instructors/MEGAN_BEA--instructor_838e6af1a533c6ccd2cd049c" }, { "instructor_uid": "instructor_c100ea542fa4e958b2305fe8", "source": "madgrades", "source_instructor_id": "5930881", "identity_basis": "source_id", "identity_status": "source_identified", "name": "XIANGCHEN LIU", "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": 3.377, "graded": 126, "counts": [ 43, 38, 20, 21, 4, 0, 0 ], "sections": 3 }, "instructor_url": "/instructors/XIANGCHEN_LIU--instructor_c100ea542fa4e958b2305fe8" }, { "instructor_uid": "instructor_3c847227bec0ee03c9b041da", "source": "madgrades", "source_instructor_id": "6286590", "identity_basis": "source_id", "identity_status": "source_identified", "name": "VIVEKANANDA DAS", "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": 3.332, "graded": 202, "counts": [ 76, 56, 32, 22, 10, 2, 4 ], "sections": 6 }, "instructor_url": "/instructors/VIVEKANANDA_DAS" }, { "instructor_uid": "instructor_e70b174ceec1b8b98f6e6ab6", "source": "madgrades", "source_instructor_id": "6362828", "identity_basis": "source_id", "identity_status": "source_identified", "name": "AKARSHIK BANERJEE", "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": 3.458, "graded": 216, "counts": [ 85, 75, 34, 13, 4, 2, 3 ], "sections": 5 }, "instructor_url": "/instructors/AKARSHIK_BANERJEE--instructor_e70b174ceec1b8b98f6e6ab6" }, { "instructor_uid": "instructor_481b909a6ae6b63737a19a5a", "source": "madgrades", "source_instructor_id": "6456467", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SAKSHAM SINGH", "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": 3.547, "graded": 253, "counts": [ 109, 91, 34, 10, 7, 2, 0 ], "sections": 8 }, "instructor_url": "/instructors/SAKSHAM_SINGH--instructor_481b909a6ae6b63737a19a5a" }, { "instructor_uid": "instructor_8bdd4bbf9e782b246177ed7c", "source": "madgrades", "source_instructor_id": "5543386", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SEIJIN NA", "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": 3.721, "graded": 301, "counts": [ 208, 58, 14, 12, 5, 3, 1 ], "sections": 8 }, "instructor_url": "/instructors/SEIJIN_NA--instructor_8bdd4bbf9e782b246177ed7c" }, { "instructor_uid": "instructor_5bea6bfaf4b60dea69142729", "source": "madgrades", "source_instructor_id": "6206470", "identity_basis": "source_id", "identity_status": "source_identified", "name": "LAURI LUOSTA", "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": 3.629, "graded": 245, "counts": [ 141, 60, 21, 14, 8, 1, 0 ], "sections": 9 }, "instructor_url": "/instructors/LAURI_LUOSTA" }, { "instructor_uid": "instructor_660469b9ff17a840f39e85dd", "source": "madgrades", "source_instructor_id": "6543932", "identity_basis": "source_id", "identity_status": "source_identified", "name": "KATIE FITZPATRICK", "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": 3.885, "graded": 161, "counts": [ 139, 13, 4, 4, 1, 0, 0 ], "sections": 15 }, "instructor_url": "/instructors/KATIE_FITZPATRICK--instructor_660469b9ff17a840f39e85dd" }, { "instructor_uid": "instructor_845a8c164af0394615fdea74", "source": "madgrades", "source_instructor_id": "6760183", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ABIGAIL ANTESANA", "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": 3.619, "graded": 147, "counts": [ 84, 31, 23, 5, 2, 2, 0 ], "sections": 3 }, "instructor_url": "/instructors/ABIGAIL_ANTESANA--instructor_845a8c164af0394615fdea74" }, { "instructor_uid": "instructor_03d1968a4896d4eb5cdc7302", "source": "madgrades", "source_instructor_id": "4576633", "identity_basis": "source_id", "identity_status": "source_identified", "name": "GISELLA KAGY", "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": 3.708, "graded": 137, "counts": [ 89, 28, 15, 2, 2, 0, 1 ], "sections": 6 }, "instructor_url": "/instructors/GISELLA_KAGY--instructor_03d1968a4896d4eb5cdc7302" }, { "instructor_uid": "instructor_b1ffb232b01eb4e08fb859f9", "source": "madgrades", "source_instructor_id": "6645461", "identity_basis": "source_id", "identity_status": "source_identified", "name": "SUPARIT SUWANIK", "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": 3.222, "graded": 133, "counts": [ 32, 56, 19, 13, 6, 3, 4 ], "sections": 4 }, "instructor_url": "/instructors/SUPARIT_SUWANIK--instructor_b1ffb232b01eb4e08fb859f9" }, { "instructor_uid": "instructor_daeda993c969642ae5ee6b88", "source": "enrollment", "source_instructor_id": "wjiang96", "identity_basis": "netid", "identity_status": "source_identified", "name": "Wanting Jiang", "email": "WJIANG96@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "instructor_url": "/instructors/WANTING_JIANG" }, { "instructor_uid": "instructor_df7ca51acf159f69bce85581", "source": "enrollment", "source_instructor_id": "mbea", "identity_basis": "netid", "identity_status": "source_identified", "name": "Megan Bea", "email": "MBEA@WISC.EDU", "first_observed_at": "2026-09-07 15:55:43.033547+00:00", "last_observed_at": "2026-09-07 15:55:43.033547+00:00", "instructor_url": "/instructors/MEGAN_BEA" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1172", "term_name": "Fall 2016", "instructors": [ "DEE WARMATH", "TAYLER NOWAK" ], "a": 13, "ab": 13, "b": 6, "bc": 5, "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": 38, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1182", "term_name": "Fall 2017", "instructors": [ "Kristin Branch", "TAYLER NOWAK" ], "a": 10, "ab": 19, "b": 1, "bc": 1, "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": 34, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1184", "term_name": "Spring 2018", "instructors": [ "DEE WARMATH", "TAYLER NOWAK" ], "a": 16, "ab": 15, "b": 4, "bc": 9, "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": 45, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1192", "term_name": "Fall 2018", "instructors": [ "Kristin Branch" ], "a": 16, "ab": 16, "b": 5, "bc": 3, "c": 1, "d": 0, "f": 0, "satisfactory": 1, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 43, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1194", "term_name": "Spring 2019", "instructors": [ "Patricia Sigler" ], "a": 23, "ab": 12, "b": 4, "bc": 2, "c": 2, "d": 2, "f": 0, "satisfactory": 2, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 47, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1202", "term_name": "Fall 2019", "instructors": [ "Yiwei Zhang" ], "a": 22, "ab": 38, "b": 20, "bc": 8, "c": 3, "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": 92, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1204", "term_name": "Spring 2020", "instructors": [ "Megan Bea" ], "a": 37, "ab": 39, "b": 11, "bc": 2, "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": 92, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1212", "term_name": "Fall 2020", "instructors": [ "XIANGCHEN LIU", "Yiwei Zhang" ], "a": 35, "ab": 20, "b": 16, "bc": 17, "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": 91, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1222", "term_name": "Fall 2021", "instructors": [ "VIVEKANANDA DAS", "Yiwei Zhang" ], "a": 18, "ab": 12, "b": 8, "bc": 4, "c": 2, "d": 1, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 46, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1224", "term_name": "Spring 2022", "instructors": [ "Megan Bea", "VIVEKANANDA DAS" ], "a": 13, "ab": 15, "b": 4, "bc": 3, "c": 2, "d": 1, "f": 1, "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": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1232", "term_name": "Fall 2022", "instructors": [ "AKARSHIK BANERJEE", "Megan Bea" ], "a": 12, "ab": 23, "b": 6, "bc": 1, "c": 0, "d": 1, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 44, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1234", "term_name": "Spring 2023", "instructors": [ "Megan Bea", "Saksham Singh" ], "a": 22, "ab": 22, "b": 7, "bc": 1, "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": 54, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1242", "term_name": "Fall 2023", "instructors": [ "Saksham Singh", "Yiwei Zhang" ], "a": 12, "ab": 11, "b": 3, "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": 29, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Megan Bea", "SeiJin Na", "XIANGCHEN LIU" ], "a": 14, "ab": 27, "b": 6, "bc": 6, "c": 3, "d": 2, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 58, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Yiwei Zhang" ], "a": 22, "ab": 11, "b": 8, "bc": 5, "c": 4, "d": 4, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 54, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Katie Fitzpatrick", "LAURI LUOSTA", "Yiwei Zhang" ], "a": 23, "ab": 18, "b": 11, "bc": 7, "c": 1, "d": 1, "f": 0, "satisfactory": 1, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 62, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Abigail Antesana", "Yiwei Zhang" ], "a": 31, "ab": 17, "b": 14, "bc": 5, "c": 2, "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": 70, "source_aliases": [ "CNSRSCI 301" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "CNSRSCI 301", "course_uid": "course_e420cb4ad0fb5cdf16dee294", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Gisella Kagy", "Suparit Suwanik", "Yiwei Zhang" ], "a": 15, "ab": 14, "b": 11, "bc": 4, "c": 1, "d": 1, "f": 3, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 49, "source_aliases": [ "CNSRSCI 301" ] } ] ``` ### statistics #### gpa 3.414 #### graded 976 #### counts * 354 * 342 * 145 * 85 * 28 * 16 * 6 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_e420cb4ad0fb5cdf16dee294-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_e420cb4ad0fb5cdf16dee294-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_e420cb4ad0fb5cdf16dee294-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_e420cb4ad0fb5cdf16dee294-0.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_e420cb4ad0fb5cdf16dee294-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_e420cb4ad0fb5cdf16dee294-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_e420cb4ad0fb5cdf16dee294-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_e420cb4ad0fb5cdf16dee294-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_e420cb4ad0fb5cdf16dee294-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_e420cb4ad0fb5cdf16dee294-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.4144467213114753 #### count 976 #### university ##### size 5151 ##### gpa Percentile 15 ##### count Percentile 89 ##### median Count 164 ##### 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 | 7 | false | | 2.8–3.2 | 266 | false | | 3.2–3.6 | 1296 | true | | 3.6–4.0 | 3581 | false | #### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 31, "gpaPercentile": 20, "countPercentile": 50, "medianCount": 976, "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": 10, "current": true }, { "range": "3.6–4.0", "count": 20, "current": false } ] } } ] ``` ### terms #### 1172 ##### term 1172 ##### gpa 3.4210526315789473 ##### count 38 ##### university ###### size 991 ###### gpa Percentile 45 ###### count Percentile 17 ###### 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 | 0 | false | | 2.4–2.8 | 22 | false | | 2.8–3.2 | 226 | false | | 3.2–3.6 | 353 | true | | 3.6–4.0 | 390 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 14, "gpaPercentile": 54, "countPercentile": 8, "medianCount": 65.5, "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": 4, "current": false }, { "range": "3.2–3.6", "count": 5, "current": true }, { "range": "3.6–4.0", "count": 5, "current": false } ] } } ] ``` #### 1182 ##### term 1182 ##### gpa 3.6129032258064515 ##### count 31 ##### university ###### size 1025 ###### gpa Percentile 61 ###### count Percentile 2 ###### 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 | 1 | false | | 2.4–2.8 | 21 | false | | 2.8–3.2 | 216 | false | | 3.2–3.6 | 369 | false | | 3.6–4.0 | 418 | true | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 17, "gpaPercentile": 63, "countPercentile": 0, "medianCount": 75, "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": 7, "current": false }, { "range": "3.6–4.0", "count": 8, "current": true } ] } } ] ``` #### 1184 ##### term 1184 ##### gpa 3.4 ##### count 45 ##### university ###### size 1010 ###### gpa Percentile 40 ###### count Percentile 27 ###### median Count 68 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 26 | false | | 2.8–3.2 | 210 | false | | 3.2–3.6 | 355 | true | | 3.6–4.0 | 418 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 17, "gpaPercentile": 25, "countPercentile": 13, "medianCount": 73, "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": 7, "current": true }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1192 ##### term 1192 ##### gpa 3.524390243902439 ##### count 41 ##### university ###### size 1077 ###### gpa Percentile 47 ###### count Percentile 22 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 22 | false | | 2.8–3.2 | 203 | false | | 3.2–3.6 | 370 | true | | 3.6–4.0 | 481 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 18, "gpaPercentile": 29, "countPercentile": 6, "medianCount": 55, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 1, "current": false }, { "range": "2.8–3.2", "count": 3, "current": false }, { "range": "3.2–3.6", "count": 6, "current": true }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1194 ##### term 1194 ##### gpa 3.488888888888889 ##### count 45 ##### university ###### size 1040 ###### gpa Percentile 47 ###### count Percentile 28 ###### median Count 67 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 23 | false | | 2.8–3.2 | 220 | false | | 3.2–3.6 | 342 | true | | 3.6–4.0 | 454 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 17, "gpaPercentile": 38, "countPercentile": 19, "medianCount": 71, "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": 8, "current": true }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1202 ##### term 1202 ##### gpa 3.347826086956522 ##### count 92 ##### university ###### size 1102 ###### gpa Percentile 33 ###### count Percentile 63 ###### median Count 68 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 14 | false | | 2.8–3.2 | 218 | false | | 3.2–3.6 | 371 | true | | 3.6–4.0 | 498 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 17, "gpaPercentile": 31, "countPercentile": 63, "medianCount": 78, "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": 3, "current": false }, { "range": "3.2–3.6", "count": 7, "current": true }, { "range": "3.6–4.0", "count": 7, "current": false } ] } } ] ``` #### 1204 ##### term 1204 ##### gpa 3.6235955056179776 ##### count 89 ##### university ###### size 1012 ###### gpa Percentile 36 ###### count Percentile 65 ###### median Count 65.5 ###### 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 | 1 | false | | 2.8–3.2 | 25 | false | | 3.2–3.6 | 301 | false | | 3.6–4.0 | 685 | true | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 17, "gpaPercentile": 19, "countPercentile": 56, "medianCount": 71, "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": 2, "current": false }, { "range": "3.6–4.0", "count": 15, "current": true } ] } } ] ``` #### 1212 ##### term 1212 ##### gpa 3.368131868131868 ##### count 91 ##### university ###### size 1111 ###### gpa Percentile 25 ###### count Percentile 61 ###### median Count 68 ###### histogram | range | count | current | | ------- | ----- | ------- | | 0.0–0.4 | 0 | false | | 0.4–0.8 | 0 | false | | 0.8–1.2 | 0 | false | | 1.2–1.6 | 0 | false | | 1.6–2.0 | 0 | false | | 2.0–2.4 | 0 | false | | 2.4–2.8 | 4 | false | | 2.8–3.2 | 159 | false | | 3.2–3.6 | 337 | true | | 3.6–4.0 | 611 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 18, "gpaPercentile": 12, "countPercentile": 53, "medianCount": 84, "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": 5, "current": true }, { "range": "3.6–4.0", "count": 13, "current": false } ] } } ] ``` #### 1222 ##### term 1222 ##### gpa 3.3260869565217392 ##### count 46 ##### university ###### size 1157 ###### gpa Percentile 24 ###### count Percentile 31 ###### 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 | true | | 3.6–4.0 | 614 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 21, "gpaPercentile": 10, "countPercentile": 25, "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": 7, "current": true }, { "range": "3.6–4.0", "count": 14, "current": false } ] } } ] ``` #### 1224 ##### term 1224 ##### gpa 3.3076923076923075 ##### count 39 ##### university ###### size 1171 ###### gpa Percentile 23 ###### count Percentile 20 ###### 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 | 3 | false | | 2.4–2.8 | 21 | false | | 2.8–3.2 | 173 | false | | 3.2–3.6 | 358 | true | | 3.6–4.0 | 616 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 20, "gpaPercentile": 5, "countPercentile": 11, "medianCount": 70.5, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 1, "current": false }, { "range": "3.2–3.6", "count": 11, "current": true }, { "range": "3.6–4.0", "count": 8, "current": false } ] } } ] ``` #### 1232 ##### term 1232 ##### gpa 3.409090909090909 ##### count 44 ##### university ###### size 1216 ###### gpa Percentile 28 ###### count Percentile 28 ###### 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 | true | | 3.6–4.0 | 670 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 20, "gpaPercentile": 16, "countPercentile": 11, "medianCount": 90.5, "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": 5, "current": true }, { "range": "3.6–4.0", "count": 14, "current": false } ] } } ] ``` #### 1234 ##### term 1234 ##### gpa 3.5462962962962963 ##### count 54 ##### university ###### size 1188 ###### gpa Percentile 40 ###### count Percentile 40 ###### 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": "CNSRSCI", "comparison": { "size": 19, "gpaPercentile": 28, "countPercentile": 17, "medianCount": 117, "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": 5, "current": true }, { "range": "3.6–4.0", "count": 13, "current": false } ] } } ] ``` #### 1242 ##### term 1242 ##### gpa 3.5344827586206895 ##### count 29 ##### departments | subject | comparison | | ------- | ---------- | | CNSRSCI | | #### 1244 ##### term 1244 ##### gpa 3.3017241379310347 ##### count 58 ##### university ###### size 1241 ###### gpa Percentile 19 ###### count Percentile 43 ###### 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": "CNSRSCI", "comparison": { "size": 23, "gpaPercentile": 14, "countPercentile": 27, "medianCount": 104, "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": 8, "current": true }, { "range": "3.6–4.0", "count": 14, "current": false } ] } } ] ``` #### 1252 ##### term 1252 ##### gpa 3.240740740740741 ##### count 54 ##### university ###### size 1333 ###### gpa Percentile 12 ###### count Percentile 38 ###### 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 | true | | 3.6–4.0 | 773 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 23, "gpaPercentile": 5, "countPercentile": 23, "medianCount": 104, "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": 4, "current": true }, { "range": "3.6–4.0", "count": 18, "current": false } ] } } ] ``` #### 1254 ##### term 1254 ##### gpa 3.418032786885246 ##### count 61 ##### university ###### size 1289 ###### gpa Percentile 26 ###### count Percentile 47 ###### 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": "CNSRSCI", "comparison": { "size": 23, "gpaPercentile": 18, "countPercentile": 27, "medianCount": 90, "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": 3, "current": false }, { "range": "3.2–3.6", "count": 7, "current": true }, { "range": "3.6–4.0", "count": 13, "current": false } ] } } ] ``` #### 1262 ##### term 1262 ##### gpa 3.4714285714285715 ##### count 70 ##### university ###### size 1320 ###### gpa Percentile 27 ###### count Percentile 49 ###### 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": "CNSRSCI", "comparison": { "size": 21, "gpaPercentile": 15, "countPercentile": 20, "medianCount": 118, "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": 11, "current": false } ] } } ] ``` #### 1264 ##### term 1264 ##### gpa 3.163265306122449 ##### count 49 ##### university ###### size 1283 ###### gpa Percentile 10 ###### count Percentile 34 ###### 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 | true | | 3.2–3.6 | 343 | false | | 3.6–4.0 | 789 | false | ##### departments ```json [ { "subject": "CNSRSCI", "comparison": { "size": 22, "gpaPercentile": 10, "countPercentile": 10, "medianCount": 105, "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": 3, "current": true }, { "range": "3.2–3.6", "count": 8, "current": false }, { "range": "3.6–4.0", "count": 10, "current": false } ] } } ] ``` ### benchmarks #### all ##### school ###### size 5151 ###### gpa 3.698259430400637 ###### top Share 84.20411888726208 ###### count 164 ##### CNSRSCI ###### size 31 ###### gpa 3.6283504025926256 ###### top Share 82.12483249501341 ###### count 976 #### terms ##### 1172 ###### school ###### size 991 ###### gpa 3.465129042641772 ###### top Share 69.42600667567366 ###### count 67 ###### CNSRSCI ###### size 14 ###### gpa 3.4758058955291706 ###### top Share 72.40039806741547 ###### count 65.5 ##### 1182 ###### school ###### size 1025 ###### gpa 3.474159360325319 ###### top Share 70.34861441764347 ###### count 69 ###### CNSRSCI ###### size 17 ###### gpa 3.5145694086277337 ###### top Share 74.60378274938202 ###### count 75 ##### 1184 ###### school ###### size 1010 ###### gpa 3.47925290354517 ###### top Share 70.86270937115944 ###### count 68 ###### CNSRSCI ###### size 17 ###### gpa 3.5513839958204554 ###### top Share 76.70287623872456 ###### count 73 ##### 1192 ###### school ###### size 1077 ###### gpa 3.50327634323125 ###### top Share 72.44641925727845 ###### count 67 ###### CNSRSCI ###### size 18 ###### gpa 3.4921746087581855 ###### top Share 74.01951479564612 ###### count 55 ##### 1194 ###### school ###### size 1040 ###### gpa 3.4906527436719808 ###### top Share 71.74728845515045 ###### count 67 ###### CNSRSCI ###### size 17 ###### gpa 3.5378693411054614 ###### top Share 76.8596088120517 ###### count 71 ##### 1202 ###### school ###### size 1102 ###### gpa 3.5102605987403313 ###### top Share 72.78244569053733 ###### count 68 ###### CNSRSCI ###### size 17 ###### gpa 3.4936403985695 ###### top Share 74.03070168013859 ###### count 78 ##### 1204 ###### school ###### size 1012 ###### gpa 3.703747431523761 ###### top Share 84.59811226304916 ###### count 65.5 ###### CNSRSCI ###### size 17 ###### gpa 3.7304394114977595 ###### top Share 89.91371180365307 ###### count 71 ##### 1212 ###### school ###### size 1111 ###### gpa 3.5856416028074487 ###### top Share 77.58926748660845 ###### count 68 ###### CNSRSCI ###### size 18 ###### gpa 3.661772272360077 ###### top Share 83.33475336135731 ###### count 84 ##### 1222 ###### school ###### size 1157 ###### gpa 3.563052311875811 ###### top Share 76.64869058732418 ###### count 64 ###### CNSRSCI ###### size 21 ###### gpa 3.6219066273341127 ###### top Share 81.61770534110484 ###### count 58 ##### 1224 ###### school ###### size 1171 ###### gpa 3.5627882428500937 ###### top Share 76.37271640560496 ###### count 64 ###### CNSRSCI ###### size 20 ###### gpa 3.5454759115101373 ###### top Share 79.46534212003172 ###### count 70.5 ##### 1232 ###### school ###### size 1216 ###### gpa 3.575457431972425 ###### top Share 77.33712216234007 ###### count 66 ###### CNSRSCI ###### size 20 ###### gpa 3.617834368808565 ###### top Share 81.83628160426352 ###### count 90.5 ##### 1234 ###### school ###### size 1188 ###### gpa 3.5799441677552393 ###### top Share 77.18256448537606 ###### count 65 ###### CNSRSCI ###### size 19 ###### gpa 3.6048767735668403 ###### top Share 80.03346364170125 ###### count 117 ##### 1242 ###### school ###### size 1295 ###### gpa 3.595302892737449 ###### top Share 78.36291889885307 ###### count 67 ###### CNSRSCI ###### size 21 ###### gpa 3.697912728932925 ###### top Share 86.42551064398879 ###### count 117 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### CNSRSCI ###### size 23 ###### gpa 3.5862228593095566 ###### top Share 79.17919283986976 ###### count 104 ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ###### CNSRSCI ###### size 23 ###### gpa 3.6691705419603458 ###### top Share 84.48369653925197 ###### count 104 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### CNSRSCI ###### size 23 ###### gpa 3.564727474066601 ###### top Share 79.63337143038319 ###### count 90 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### CNSRSCI ###### size 21 ###### gpa 3.6261464494189632 ###### top Share 81.76866165097593 ###### count 118 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ###### CNSRSCI ###### size 22 ###### gpa 3.51605863991461 ###### top Share 75.92309209656172 ###### count 105 ## instructor Trends ```json [ { "uid": "instructor_4214af0bd920d2865ac013b5", "name": "YIWEI ZHANG", "count": 461, "terms": [ { "term": "1202", "count": 92, "sections": 2, "gpa": 3.347826086956522 }, { "term": "1212", "count": 91, "sections": 1, "gpa": 3.368131868131868 }, { "term": "1222", "count": 46, "sections": 2, "gpa": 3.3260869565217392 }, { "term": "1242", "count": 29, "sections": 2, "gpa": 3.5344827586206895 }, { "term": "1252", "count": 54, "sections": 2, "gpa": 3.240740740740741 }, { "term": "1254", "count": 43, "sections": 2, "gpa": 3.4651162790697674 }, { "term": "1262", "count": 70, "sections": 1, "gpa": 3.4714285714285715 }, { "term": "1264", "count": 36, "sections": 1, "gpa": 3.138888888888889 } ] }, { "uid": "instructor_838e6af1a533c6ccd2cd049c", "name": "MEGAN BEA", "count": 249, "terms": [ { "term": "1204", "count": 89, "sections": 2, "gpa": 3.6235955056179776 }, { "term": "1224", "count": 39, "sections": 1, "gpa": 3.3076923076923075 }, { "term": "1232", "count": 44, "sections": 1, "gpa": 3.409090909090909 }, { "term": "1234", "count": 54, "sections": 2, "gpa": 3.5462962962962963 }, { "term": "1244", "count": 23, "sections": 1, "gpa": 3.152173913043478 } ] }, { "uid": "instructor_c100ea542fa4e958b2305fe8", "name": "XIANGCHEN LIU", "count": 126, "terms": [ { "term": "1212", "count": 91, "sections": 1, "gpa": 3.368131868131868 }, { "term": "1244", "count": 35, "sections": 2, "gpa": 3.4 } ] }, { "uid": "instructor_02b717bc90cf7826f7a66079", "name": "TAYLER NOWAK", "count": 114, "terms": [ { "term": "1172", "count": 38, "sections": 1, "gpa": 3.4210526315789473 }, { "term": "1182", "count": 31, "sections": 1, "gpa": 3.6129032258064515 }, { "term": "1184", "count": 45, "sections": 1, "gpa": 3.4 } ] }, { "uid": "instructor_3c847227bec0ee03c9b041da", "name": "VIVEKANANDA DAS", "count": 85, "terms": [ { "term": "1222", "count": 46, "sections": 2, "gpa": 3.3260869565217392 }, { "term": "1224", "count": 39, "sections": 1, "gpa": 3.3076923076923075 } ] }, { "uid": "instructor_0528d1d144df225fe51d3519", "name": "DEE WARMATH", "count": 83, "terms": [ { "term": "1172", "count": 38, "sections": 1, "gpa": 3.4210526315789473 }, { "term": "1184", "count": 45, "sections": 1, "gpa": 3.4 } ] }, { "uid": "instructor_481b909a6ae6b63737a19a5a", "name": "SAKSHAM SINGH", "count": 83, "terms": [ { "term": "1234", "count": 54, "sections": 2, "gpa": 3.5462962962962963 }, { "term": "1242", "count": 29, "sections": 2, "gpa": 3.5344827586206895 } ] }, { "uid": "instructor_acf0bf2387eac107d4ce4749", "name": "KRISTIN BRANCH", "count": 72, "terms": [ { "term": "1182", "count": 31, "sections": 1, "gpa": 3.6129032258064515 }, { "term": "1192", "count": 41, "sections": 1, "gpa": 3.524390243902439 } ] }, { "uid": "instructor_845a8c164af0394615fdea74", "name": "ABIGAIL ANTESANA", "count": 70, "terms": [ { "term": "1262", "count": 70, "sections": 1, "gpa": 3.4714285714285715 } ] }, { "uid": "instructor_5bea6bfaf4b60dea69142729", "name": "LAURI LUOSTA", "count": 61, "terms": [ { "term": "1254", "count": 61, "sections": 3, "gpa": 3.418032786885246 } ] }, { "uid": "instructor_8bdd4bbf9e782b246177ed7c", "name": "SEIJIN NA", "count": 58, "terms": [ { "term": "1244", "count": 58, "sections": 3, "gpa": 3.3017241379310347 } ] }, { "uid": "instructor_b1ffb232b01eb4e08fb859f9", "name": "SUPARIT SUWANIK", "count": 49, "terms": [ { "term": "1264", "count": 49, "sections": 2, "gpa": 3.163265306122449 } ] }, { "uid": "instructor_dcc1a85d04f35e1240ed8a6d", "name": "PATRICIA SIGLER", "count": 45, "terms": [ { "term": "1194", "count": 45, "sections": 1, "gpa": 3.488888888888889 } ] }, { "uid": "instructor_e70b174ceec1b8b98f6e6ab6", "name": "AKARSHIK BANERJEE", "count": 44, "terms": [ { "term": "1232", "count": 44, "sections": 1, "gpa": 3.409090909090909 } ] }, { "uid": "instructor_660469b9ff17a840f39e85dd", "name": "KATIE FITZPATRICK", "count": 18, "terms": [ { "term": "1254", "count": 18, "sections": 1, "gpa": 3.3055555555555554 } ] }, { "uid": "instructor_03d1968a4896d4eb5cdc7302", "name": "GISELLA KAGY", "count": 13, "terms": [ { "term": "1264", "count": 13, "sections": 1, "gpa": 3.230769230769231 } ] } ] ``` ## following None recorded. ## projection ### target 1272 ### interval #### lower 3.22 #### upper 3.52 #### coverage 80 #### terms 5 ### gpa 3.370188302025229 ### grades | grade | percentage | | ----- | ------------------ | | A | 38.74242376068699 | | AB | 29.604701143525226 | | B | 16.762693904204447 | | BC | 6.929872600898876 | | C | 3.729388800674296 | | D | 3.3611403412275336 | | F | 0.8697794487826302 | ### source Terms * 1262 * 1252 * 1232 * 1222 ### source Count 214 ### same Season true ### historical Range * 3.240740740740741 * 3.471428571428571 ### backtest #### terms 5 #### gpa Error 0.096585764470501 #### mix Error 17.812672416128546