# STAT 575: Statistical Methods for Spatial Data | UW–Madison [View on UW Courses](https://uwcourses.com/courses/STAT_575) ## 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 0189d78d9684ee96f0d21de2e2829814a5dfd69dedee849a69e20fb257e9e878 ### course id STAT 575 ### course uid course\_60dd4194a1aff4f2fbca49f8 ### catalog version id 4a74b7e1b64e4dd7c7e55f2a7f0034f8563fbc5f22ea65e576eb385ca52b0edb ### course number 575 ### subjects * STAT ### title STATISTICAL METHODS FOR SPATIAL DATA ### description Detecting, quantifying, and modeling spatial patterns and structure in data. Variograms and covariance functions, linear predictions with uncertainty qualification, and conditional simulations. Spectral domain models and spectral densities. Spatial point processes. Contemporary applications and Gaussian process model fitting at scale. ### requirements text (STAT 333or340) and (MATH 320,340,341,345, or375), graduate/professional standing, or declared in Statistics VISP ### credit offering ids None recorded. ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 71c4502c815b1d6596c2e714c9ad1e5a590da9b5761ee83a0181847c82154699 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary STAT 575 teaches methods for detecting, quantifying, and modeling spatial patterns, including variograms, covariance functions, and Gaussian processes. ### llm topics * Variograms and covariance functions * Spectral domain models * Spatial point processes * Gaussian process model fitting ### llm skills * Detecting and quantifying spatial patterns * Modeling spatial structure with variograms and covariance functions * Analyzing spectral domain models * Modeling spatial point processes * Fitting Gaussian process models at scale ### llm assumed background * Regression analysis and statistical modeling using R * Linear algebra and multivariate calculus ### llm search phrases * spatial statistics * geostatistics * variogram modeling * Gaussian processes * spatial point processes * kriging * spatial data analysis ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash 918f91e3337d927cbc12f2fbb1a5ac972cd5d1ff6da597bfe982f1b649114885 #### course id STAT 575 #### 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 — Fall 2015: 3.66 GPA, 91.2% A/AB (n=34 letter grades); Spring 2024: 3.31 GPA, 66.7% A/AB (n=27 letter grades); Fall 2025: 3.33 GPA, 61.1% A/AB (n=18 letter grades). ```json { "citations": [ { "course_id": "STAT 575", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "185351f4-8b5f-3dbb-9474-aa16351e3ba0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1162", "type": "grade" }, { "course_id": "STAT 575", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "185351f4-8b5f-3dbb-9474-aa16351e3ba0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1244", "type": "grade" }, { "course_id": "STAT 575", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "185351f4-8b5f-3dbb-9474-aa16351e3ba0", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" } ] } ``` #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history None recorded. #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [ "n1", "n2", "n3" ], "condition": null, "course": null, "evidence": "(STAT 333or340) and (MATH 320,340,341,345, or375), graduate/professional standing, or declared in Statistics VISP", "id": "n0", "kind": "any" }, { "children": [ "n4", "n5" ], "condition": null, "course": null, "evidence": "(STAT 333or340) and (MATH 320,340,341,345, or375)", "id": "n1", "kind": "all" }, { "children": [], "condition": "graduate/professional standing", "course": null, "evidence": "graduate/professional standing", "id": "n2", "kind": "condition" }, { "children": [], "condition": "declared in Statistics VISP", "course": null, "evidence": "declared in Statistics VISP", "id": "n3", "kind": "condition" }, { "children": [ "n11", "n12" ], "condition": null, "course": null, "evidence": "STAT 333or340", "id": "n4", "kind": "any" }, { "children": [ "n6", "n7", "n8", "n9", "n10" ], "condition": null, "course": null, "evidence": "MATH 320,340,341,345, or375", "id": "n5", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 320, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "MATH 320", "id": "n6", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 340, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "340", "id": "n7", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 341, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "341", "id": "n8", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 345, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "345", "id": "n9", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 375, "minimum_grade": null, "subjects": [ "MATH" ], "timing": "prior" }, "evidence": "375", "id": "n10", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 333, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "STAT 333or340", "id": "n11", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 340, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "STAT 333or340", "id": "n12", "kind": "course" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors None recorded. ### offerings None recorded. ### sections None recorded. ### grade instructors ```json [ { "instructor_uid": "instructor_e15e1a245191e94e0325d0f0", "source": "madgrades", "source_instructor_id": "321374", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JUN ZHU", "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": 3.543, "graded": 483, "counts": [ 178, 184, 110, 7, 4, 0, 0 ], "sections": 61 }, "instructor_url": "/instructors/JUN_ZHU--instructor_e15e1a245191e94e0325d0f0" }, { "instructor_uid": "instructor_a67bc730d867a331aa80cc3e", "source": "madgrades", "source_instructor_id": "3457484", "identity_basis": "source_id", "identity_status": "source_identified", "name": "YANBING ZHENG", "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": 13, "counts": [ 6, 6, 1, 0, 0, 0, 0 ], "sections": 1 }, "instructor_url": "/instructors/YANBING_ZHENG--instructor_a67bc730d867a331aa80cc3e" }, { "instructor_uid": "instructor_8059223b542b6452f4aa2cae", "source": "madgrades", "source_instructor_id": "893827", "identity_basis": "source_id", "identity_status": "source_identified", "name": "RONALD GANGNON", "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": 3.641, "graded": 456, "counts": [ 229, 138, 82, 5, 1, 1, 0 ], "sections": 98 }, "instructor_url": "/instructors/RONALD_GANGNON" }, { "instructor_uid": "instructor_a6ceb9dbcbb9539d970f1bbb", "source": "madgrades", "source_instructor_id": "6586881", "identity_basis": "source_id", "identity_status": "source_identified", "name": "CHRISTOPHER GEOGA", "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": 3.564, "graded": 110, "counts": [ 65, 18, 14, 6, 5, 2, 0 ], "sections": 12 }, "instructor_url": "/instructors/CHRISTOPHER_GEOGA--instructor_a6ceb9dbcbb9539d970f1bbb" }, { "instructor_uid": "instructor_b9ef32aedc384ae4b8d3024a", "source": "madgrades", "source_instructor_id": "6239709", "identity_basis": "source_id", "identity_status": "source_identified", "name": "XINRAN MIAO", "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": 3.315, "graded": 27, "counts": [ 14, 4, 1, 3, 4, 1, 0 ], "sections": 2 }, "instructor_url": "/instructors/XINRAN_MIAO--instructor_b9ef32aedc384ae4b8d3024a" }, { "instructor_uid": "instructor_621aac63e181a381dfd799b2", "source": "madgrades", "source_instructor_id": "6452326", "identity_basis": "source_id", "identity_status": "source_identified", "name": "HAORAN XIONG", "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": 3.333, "graded": 18, "counts": [ 9, 2, 3, 2, 1, 1, 0 ], "sections": 2 }, "instructor_url": "/instructors/HAORAN_XIONG--instructor_621aac63e181a381dfd799b2" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1072", "term_name": "Fall 2006", "instructors": [ "Jun Zhu" ], "a": 21, "ab": 4, "b": 1, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 2, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 28, "source_aliases": [ "STAT 575" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1092", "term_name": "Fall 2008", "instructors": [ "Jun Zhu" ], "a": 7, "ab": 6, "b": 0, "bc": 0, "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": 16, "source_aliases": [ "STAT 575" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1122", "term_name": "Fall 2011", "instructors": [ "Jun Zhu" ], "a": 12, "ab": 8, "b": 1, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 1, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 22, "source_aliases": [ "STAT 575" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1144", "term_name": "Spring 2014", "instructors": [ "YANBING ZHENG" ], "a": 6, "ab": 6, "b": 1, "bc": 0, "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": 16, "source_aliases": [ "STAT 575" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1162", "term_name": "Fall 2015", "instructors": [ "RONALD GANGNON" ], "a": 14, "ab": 17, "b": 3, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 4, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 1, "no_work": 0, "not_reported": 0, "other": 0, "total": 39, "source_aliases": [ "STAT 575" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1244", "term_name": "Spring 2024", "instructors": [ "Christopher Geoga", "XINRAN MIAO" ], "a": 14, "ab": 4, "b": 1, "bc": 3, "c": 4, "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": 27, "source_aliases": [ "STAT 575" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 575", "course_uid": "course_60dd4194a1aff4f2fbca49f8", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Christopher Geoga", "Haoran Xiong" ], "a": 9, "ab": 2, "b": 3, "bc": 2, "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": 18, "source_aliases": [ "STAT 575" ] } ] ``` ### statistics #### gpa 3.625 #### graded 152 #### counts * 83 * 47 * 10 * 5 * 5 * 2 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_60dd4194a1aff4f2fbca49f8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_60dd4194a1aff4f2fbca49f8-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_60dd4194a1aff4f2fbca49f8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_60dd4194a1aff4f2fbca49f8-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_60dd4194a1aff4f2fbca49f8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_60dd4194a1aff4f2fbca49f8-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.625 #### count 152 #### university ##### size 3424 ##### gpa Percentile 44 ##### count Percentile 66 ##### median Count 95 ##### 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 | 18 | false | | 2.8–3.2 | 346 | false | | 3.2–3.6 | 1071 | false | | 3.6–4.0 | 1989 | true | #### departments ```json [ { "subject": "STAT", "comparison": { "size": 57, "gpaPercentile": 66, "countPercentile": 57, "medianCount": 127, "histogram": [ { "range": "0.0–0.4", "count": 0, "current": false }, { "range": "0.4–0.8", "count": 0, "current": false }, { "range": "0.8–1.2", "count": 0, "current": false }, { "range": "1.2–1.6", "count": 0, "current": false }, { "range": "1.6–2.0", "count": 0, "current": false }, { "range": "2.0–2.4", "count": 0, "current": false }, { "range": "2.4–2.8", "count": 0, "current": false }, { "range": "2.8–3.2", "count": 9, "current": false }, { "range": "3.2–3.6", "count": 25, "current": false }, { "range": "3.6–4.0", "count": 23, "current": true } ] } } ] ``` ### terms #### 1072 ##### term 1072 ##### gpa 3.8846153846153846 ##### count 26 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1092 ##### term 1092 ##### gpa 3.769230769230769 ##### count 13 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1122 ##### term 1122 ##### gpa 3.761904761904762 ##### count 21 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1144 ##### term 1144 ##### gpa 3.6923076923076925 ##### count 13 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1162 ##### term 1162 ##### gpa 3.661764705882353 ##### count 34 ##### university ###### size 954 ###### gpa Percentile 69 ###### count Percentile 8 ###### median Count 64.5 ###### 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 | 2 | false | | 2.4–2.8 | 23 | false | | 2.8–3.2 | 234 | false | | 3.2–3.6 | 350 | false | | 3.6–4.0 | 345 | true | ##### departments ```json [ { "subject": "STAT", "comparison": { "size": 24, "gpaPercentile": 83, "countPercentile": 9, "medianCount": 50.5, "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": 5, "current": false }, { "range": "3.2–3.6", "count": 14, "current": false }, { "range": "3.6–4.0", "count": 5, "current": true } ] } } ] ``` #### 1244 ##### term 1244 ##### gpa 3.314814814814815 ##### count 27 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1262 ##### term 1262 ##### gpa 3.3333333333333335 ##### count 18 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | ### benchmarks #### all ##### school ###### size 3424 ###### gpa 3.6159164037496665 ###### top Share 79.03509629289547 ###### count 95 ##### STAT ###### size 57 ###### gpa 3.503773675020082 ###### top Share 72.43046478988659 ###### count 127 #### terms ##### 1072 ###### school ###### size 723 ###### gpa 3.344595727439471 ###### top Share 62.012941427864526 ###### count 67 ##### 1092 ###### school ###### size 732 ###### gpa 3.374660709520374 ###### top Share 63.690339324346596 ###### count 70 ###### STAT ###### size 11 ###### gpa 3.2851296989222463 ###### top Share 61.121424545066226 ###### count 65 ##### 1122 ###### school ###### size 804 ###### gpa 3.3737149752667013 ###### top Share 63.65118790117902 ###### count 70 ###### STAT ###### size 14 ###### gpa 3.247214504889537 ###### top Share 58.600170104917346 ###### count 78.5 ##### 1144 ###### school ###### size 878 ###### gpa 3.4092443327803017 ###### top Share 65.95978235963416 ###### count 64 ###### STAT ###### size 14 ###### gpa 3.0970281238579784 ###### top Share 51.741770775379614 ###### count 74.5 ##### 1162 ###### school ###### size 954 ###### gpa 3.43726781345039 ###### top Share 68.05645304987395 ###### count 64.5 ###### STAT ###### size 24 ###### gpa 3.394300783591793 ###### top Share 65.51183483352922 ###### count 50.5 ##### 1244 ###### school ###### size 1241 ###### gpa 3.5975573126929192 ###### top Share 78.29036874847135 ###### count 65 ###### STAT ###### size 29 ###### gpa 3.390846810323202 ###### top Share 64.2629736611174 ###### count 62 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### STAT ###### size 29 ###### gpa 3.415022952129974 ###### top Share 64.95385808199006 ###### count 81 ## instructor Trends ```json [ { "uid": "instructor_e15e1a245191e94e0325d0f0", "name": "JUN ZHU", "count": 60, "terms": [ { "term": "1072", "count": 26, "sections": 1, "gpa": 3.8846153846153846 }, { "term": "1092", "count": 13, "sections": 1, "gpa": 3.769230769230769 }, { "term": "1122", "count": 21, "sections": 1, "gpa": 3.761904761904762 } ] }, { "uid": "instructor_a6ceb9dbcbb9539d970f1bbb", "name": "CHRISTOPHER GEOGA", "count": 45, "terms": [ { "term": "1244", "count": 27, "sections": 2, "gpa": 3.314814814814815 }, { "term": "1262", "count": 18, "sections": 2, "gpa": 3.3333333333333335 } ] }, { "uid": "instructor_8059223b542b6452f4aa2cae", "name": "RONALD GANGNON", "count": 34, "terms": [ { "term": "1162", "count": 34, "sections": 1, "gpa": 3.661764705882353 } ] }, { "uid": "instructor_b9ef32aedc384ae4b8d3024a", "name": "XINRAN MIAO", "count": 27, "terms": [ { "term": "1244", "count": 27, "sections": 2, "gpa": 3.314814814814815 } ] }, { "uid": "instructor_621aac63e181a381dfd799b2", "name": "HAORAN XIONG", "count": 18, "terms": [ { "term": "1262", "count": 18, "sections": 2, "gpa": 3.3333333333333335 } ] }, { "uid": "instructor_a67bc730d867a331aa80cc3e", "name": "YANBING ZHENG", "count": 13, "terms": [ { "term": "1144", "count": 13, "sections": 1, "gpa": 3.6923076923076925 } ] } ] ``` ## following None recorded.