# STAT 701: Applied Time Series Analysis, Forecasting and Control I | UW–Madison [View on UW Courses](https://uwcourses.com/courses/STAT_701) ## 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 c3667663d1bd701b0e88f49701cc53b28df84612dfd63fed00534c187a900850 ### course id STAT 701 ### course uid course\_98c8f7223e5e4f977f8032c8 ### catalog version id 854403f3f4254a78dc94a24d12bc50f64f68e59a70a7edbdeec41d5068f026f6 ### course number 701 ### subjects * STAT ### title APPLIED TIME SERIES ANALYSIS, FORECASTING AND CONTROL I ### description Theory and application of discrete time series models illustrated with forecasting problems. Principles of iterative model building. Representation of dynamic relations by difference equations. Autoregressive integrated Moving Average models. Identification, fitting, diagnostic checking of models. Seasonal model application to forecasting in business, economics, ecology, and engineering used at each stage, which the student analyzes using computer programs which have been specially written and extensively tested. ### requirements text Graduate/professional standing ### credits min 3 ### credits max 3 ### credit offering ids * 1272:932:018489 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 778ce63e5edfdf12d6a817554ad1830297bc9578fc0e8b178638efa8dfcaf7b2 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary STAT 701 covers the theory and application of discrete time series models, focusing on forecasting, model building, and diagnostic checking. ### llm topics * Dynamic relations by difference equations * Autoregressive integrated Moving Average (ARIMA) models * Seasonal model application ### llm skills * Theory and application of discrete time series models * Principles of iterative model building * Identification, fitting, and diagnostic checking of models * Seasonal model application to forecasting ### llm assumed background None recorded. ### llm search phrases * time series analysis * forecasting models * ARIMA models * statistical modeling * difference equations ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash 9f5f9b5d7c515fa96f206433167f0233f33c4cb5b28ede4a34320334841b3e42 #### course id STAT 701 #### current instructors ```json [ { "instructor_uid": "instructor_7eca2811645c15f0e8db796e", "message": "No course-specific reviews available", "name": "Christopher Geoga", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [ { "citations": [ { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" } ], "text": "Recent recorded grades — Fall 2023: 4.00 GPA, 100.0% A/AB (n=11 letter grades); Spring 2025: 3.67 GPA, 77.8% A/AB (n=18 letter grades)." } ] } ] ``` #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered true #### profile hash 5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02 #### quick take Recent recorded grades — Spring 2022: 3.88 GPA, 94.1% A/AB (n=17 letter grades); Fall 2023: 4.00 GPA, 100.0% A/AB (n=11 letter grades); Spring 2025: 3.67 GPA, 77.8% A/AB (n=18 letter grades). ```json { "citations": [ { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1224", "type": "grade" }, { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" } ] } ``` #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history CHRISTOPHER GEOGA is recorded teaching in Fall 2023, Spring 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "STAT 701", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "source_record": { "entity_id": "3932776f-ebf8-3a23-b066-29b1784b69b2", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1254", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [], "condition": "Graduate/professional standing", "course": null, "evidence": "Graduate/professional standing", "id": "n0", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors | instructor\_uid | source | source\_instructor\_id | identity\_basis | identity\_status | name | email | first\_observed\_at | last\_observed\_at | instructor\_url | | ------------------------------------ | ---------- | ---------------------- | --------------- | ------------------ | ----------------- | --------------- | -------------------------------- | -------------------------------- | ------------------------------- | | instructor\_7eca2811645c15f0e8db796e | enrollment | geoga | netid | source\_identified | Christopher Geoga | GEOGA\@WISC.EDU | 2026-09-07 15:55:43.033547+00:00 | 2026-09-07 15:55:43.033547+00:00 | /instructors/CHRISTOPHER\_GEOGA | ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:932:018489", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1272", "source_course_id": "018489", "source_subject_id": "932", "title": "Applied Time Series Analysis, Forecasting and Control I", "credits_min": 3, "credits_max": 3, "typically_offered": "Occasionally" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:34648", "term_id": "1272", "source_section_id": "34648", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 30, "enrolled": 29, "waitlisted": 1, "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_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_028f5fb1497f12d2f925d786", "source": "madgrades", "source_instructor_id": "4695492", "identity_basis": "source_id", "identity_status": "source_identified", "name": "YAZHEN WANG", "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": 10, "quality": 2.9, "difficulty": 3, "quality_count": 10, "difficulty_count": 10, "profile_id": "rmp:1357778", "source_url": "https://www.ratemyprofessors.com/professor/1357778", "match_basis": "exact_name", "observed_at": "2026-09-07 15:58:01.601642+00:00", "courses": { "course_c3af14b05ef6845e7d2ecd4d": { "review_count": 2, "quality": 1, "difficulty": 4.5, "quality_count": 2, "difficulty_count": 2 }, "course_3aa77a7c307c944aec9fad7e": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_1282dc8dbc1e7c5749f7cc41": { "review_count": 1, "quality": 2, "difficulty": 2, "quality_count": 1, "difficulty_count": 1 }, "course_2a00c702ff402614a950606e": { "review_count": 3, "quality": 3.67, "difficulty": 2.67, "quality_count": 3, "difficulty_count": 3 }, "course_1b76508145789f8fbc49d1fa": { "review_count": 2, "quality": 2, "difficulty": 3, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.4064571890310638, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.148, "graded": 908, "counts": [ 357, 96, 250, 18, 119, 61, 7 ], "sections": 64 }, "instructor_url": "/instructors/YAZHEN_WANG--instructor_028f5fb1497f12d2f925d786" }, { "instructor_uid": "instructor_1dadda4e80ccda3b00d60248", "source": "madgrades", "source_instructor_id": "3783301", "identity_basis": "source_id", "identity_status": "source_identified", "name": "FANGFANG WANG", "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": 2, "quality": 3, "difficulty": 4.5, "quality_count": 2, "difficulty_count": 2, "profile_id": "rmp:2346125", "source_url": "https://www.ratemyprofessors.com/professor/2346125", "match_basis": "exact_name", "observed_at": "2026-09-07 16:39:23.508204+00:00", "courses": { "course_8f1b73751758944263fbb9e1": { "review_count": 2, "quality": 3, "difficulty": 4.5, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.5997143486787233, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.565, "graded": 201, "counts": [ 84, 76, 30, 7, 3, 1, 0 ], "sections": 6 }, "instructor_url": "/instructors/FANGFANG_WANG" }, { "instructor_uid": "instructor_65cbac2c9da9e3d3236992ef", "source": "madgrades", "source_instructor_id": "4108525", "identity_basis": "source_id", "identity_status": "source_identified", "name": "ZHENGJUN 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", "grade_statistics": { "gpa": 3.47, "graded": 1374, "counts": [ 541, 447, 245, 81, 44, 14, 2 ], "sections": 96 }, "instructor_url": "/instructors/ZHENGJUN_ZHANG--instructor_65cbac2c9da9e3d3236992ef" }, { "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_7eca2811645c15f0e8db796e", "source": "enrollment", "source_instructor_id": "geoga", "identity_basis": "netid", "identity_status": "source_identified", "name": "Christopher Geoga", "email": "GEOGA@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/CHRISTOPHER_GEOGA" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1074", "term_name": "Spring 2007", "instructors": [ "Jun Zhu" ], "a": 7, "ab": 6, "b": 4, "bc": 1, "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": 19, "source_aliases": [ "STAT 701" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1112", "term_name": "Fall 2010", "instructors": [ "Yazhen Wang" ], "a": 25, "ab": 0, "b": 3, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 28, "source_aliases": [ "STAT 701" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1182", "term_name": "Fall 2017", "instructors": [ "FANGFANG WANG" ], "a": 15, "ab": 7, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 22, "source_aliases": [ "STAT 701" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1192", "term_name": "Fall 2018", "instructors": [ "FANGFANG WANG" ], "a": 11, "ab": 14, "b": 2, "bc": 0, "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": 28, "source_aliases": [ "STAT 701" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1224", "term_name": "Spring 2022", "instructors": [ "Zheng Zhang" ], "a": 16, "ab": 0, "b": 0, "bc": 0, "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": 17, "source_aliases": [ "STAT 701" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1242", "term_name": "Fall 2023", "instructors": [ "Christopher Geoga" ], "a": 11, "ab": 0, "b": 0, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 11, "source_aliases": [ "STAT 701" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "STAT 701", "course_uid": "course_98c8f7223e5e4f977f8032c8", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Christopher Geoga" ], "a": 10, "ab": 4, "b": 4, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 18, "source_aliases": [ "STAT 701" ] } ] ``` ### statistics #### gpa 3.761 #### graded 142 #### counts * 95 * 31 * 13 * 1 * 2 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_98c8f7223e5e4f977f8032c8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_98c8f7223e5e4f977f8032c8-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_98c8f7223e5e4f977f8032c8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_98c8f7223e5e4f977f8032c8-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_98c8f7223e5e4f977f8032c8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_98c8f7223e5e4f977f8032c8-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_98c8f7223e5e4f977f8032c8-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_98c8f7223e5e4f977f8032c8-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.76056338028169 #### count 142 #### university ##### size 3704 ##### gpa Percentile 59 ##### count Percentile 63 ##### median Count 96 ##### 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 | 18 | false | | 2.8–3.2 | 340 | false | | 3.2–3.6 | 1112 | false | | 3.6–4.0 | 2233 | true | #### departments ```json [ { "subject": "STAT", "comparison": { "size": 60, "gpaPercentile": 71, "countPercentile": 51, "medianCount": 138.5, "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": 8, "current": false }, { "range": "3.2–3.6", "count": 25, "current": false }, { "range": "3.6–4.0", "count": 27, "current": true } ] } } ] ``` ### terms #### 1074 ##### term 1074 ##### gpa 3.5277777777777777 ##### count 18 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1112 ##### term 1112 ##### gpa 3.892857142857143 ##### count 28 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1182 ##### term 1182 ##### gpa 3.840909090909091 ##### count 22 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1192 ##### term 1192 ##### gpa 3.607142857142857 ##### count 28 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1224 ##### term 1224 ##### gpa 3.8823529411764706 ##### count 17 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1242 ##### term 1242 ##### gpa 4 ##### count 11 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | #### 1254 ##### term 1254 ##### gpa 3.6666666666666665 ##### count 18 ##### departments | subject | comparison | | ------- | ---------- | | STAT | | ### benchmarks #### all ##### school ###### size 3704 ###### gpa 3.635282750755212 ###### top Share 80.39793207181239 ###### count 96 ##### STAT ###### size 60 ###### gpa 3.5458369397663634 ###### top Share 74.71658481517133 ###### count 138.5 #### terms ##### 1074 ###### school ###### size 695 ###### gpa 3.3616924722887376 ###### top Share 63.22509110105764 ###### count 69 ##### 1112 ###### school ###### size 805 ###### gpa 3.3737773184830386 ###### top Share 63.91039244872789 ###### count 66 ###### STAT ###### size 14 ###### gpa 3.242406375705586 ###### top Share 57.34276482904032 ###### count 68.5 ##### 1182 ###### school ###### size 1025 ###### gpa 3.474159360325319 ###### top Share 70.34861441764347 ###### count 69 ###### STAT ###### size 24 ###### gpa 3.4023821420534044 ###### top Share 65.90044412864664 ###### count 65.5 ##### 1192 ###### school ###### size 1077 ###### gpa 3.50327634323125 ###### top Share 72.44641925727845 ###### count 67 ###### STAT ###### size 27 ###### gpa 3.349790708103796 ###### top Share 62.94637491184082 ###### count 74 ##### 1224 ###### school ###### size 1171 ###### gpa 3.5627882428500937 ###### top Share 76.37271640560496 ###### count 64 ###### STAT ###### size 27 ###### gpa 3.4650681869904103 ###### top Share 69.88606041738046 ###### count 74 ##### 1242 ###### school ###### size 1295 ###### gpa 3.595302892737449 ###### top Share 78.36291889885307 ###### count 67 ###### STAT ###### size 34 ###### gpa 3.4558758327213903 ###### top Share 69.10154863162224 ###### count 55 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ###### STAT ###### size 28 ###### gpa 3.4752654121860003 ###### top Share 68.35873780152826 ###### count 70 ## instructor Trends ```json [ { "uid": "instructor_1dadda4e80ccda3b00d60248", "name": "FANGFANG WANG", "count": 50, "terms": [ { "term": "1182", "count": 22, "sections": 1, "gpa": 3.840909090909091 }, { "term": "1192", "count": 28, "sections": 1, "gpa": 3.607142857142857 } ] }, { "uid": "instructor_a6ceb9dbcbb9539d970f1bbb", "name": "CHRISTOPHER GEOGA", "count": 29, "terms": [ { "term": "1242", "count": 11, "sections": 1, "gpa": 4 }, { "term": "1254", "count": 18, "sections": 1, "gpa": 3.6666666666666665 } ] }, { "uid": "instructor_028f5fb1497f12d2f925d786", "name": "YAZHEN WANG", "count": 28, "terms": [ { "term": "1112", "count": 28, "sections": 1, "gpa": 3.892857142857143 } ] }, { "uid": "instructor_e15e1a245191e94e0325d0f0", "name": "JUN ZHU", "count": 18, "terms": [ { "term": "1074", "count": 18, "sections": 1, "gpa": 3.5277777777777777 } ] }, { "uid": "instructor_65cbac2c9da9e3d3236992ef", "name": "ZHENGJUN ZHANG", "count": 17, "terms": [ { "term": "1224", "count": 17, "sections": 1, "gpa": 3.8823529411764706 } ] } ] ``` ## following | code | title | | -------- | ----------------------------- | | STAT 801 | ADVANCED FINANCIAL STATISTICS |