# ACTSCI 640: Actuarial Statistics for Risk Modeling | UW–Madison [View on UW Courses](https://uwcourses.com/courses/ACTSCI_640) ## 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 258eaffa1ce419716c31379b486edf3935234eadd75c9bf17b87119df332dccb ### course id ACTSCI 640 ### course uid course\_09c6ee1bc749ac38c1a7d335 ### catalog version id c49d54142efd0a8e8fc3933449f096416029830f8dbee25000df802a58f756a8 ### course number 640 ### subjects * ACTSCI ### title ACTUARIAL STATISTICS FOR RISK MODELING ### description Introduction to statistical learning theory and methods for analyzing and modeling risks in actuarial applications. Topics include linear and nonlinear models; diagnostics and assessment of predictive models; variable and model selection; and non-supervised learning techniques. ### requirements text (GEN BUS 317,ECON 410,STAT/​MATH  310,STAT 312,333, or340), graduate/professional standing, or declared in Capstone Certificate in Actuarial Science ### credits min 4 ### credits max 4 ### credit offering ids * 1272:242:026740 ### llm job id enrich-8b774950c2b6adfdc46d1b82 ### llm output id 3cd9a665ed1b94bcf340fe295a98785b7d3bf0d40dddb2b4ff660f1984dcc662 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Introduces statistical learning theory and methods for analyzing and modeling risks in actuarial applications. ### llm topics * Linear and nonlinear models, diagnostics, variable selection, and non-supervised learning. ### llm skills * Statistical learning theory and methods for analyzing and modeling risks. * Diagnostics, assessment, variable selection, and non-supervised learning techniques. ### llm assumed background * Linear and nonlinear regression models, model diagnostics, and variable selection techniques. * Proficiency in the R programming language for statistical computing. * Probability theory, statistical inference, and simulation methods. ### llm search phrases * actuarial risk modeling statistical learning * predictive model diagnostics actuarial science * non-supervised learning techniques risk assessment * variable selection methods actuarial applications ### llm requirements status valid ### llm student summary status valid ### llm experience status insufficient\_evidence ### catalog variants None recorded. ### student summary #### context hash efb41ff57fcfcf8a4be8ec04843a00c3a5eeeeaed802c3ebcc5f58624ae572c3 #### course id ACTSCI 640 #### current instructors ```json [ { "instructor_uid": "instructor_897686e4d69a5b75903adc7a", "message": "No course-specific reviews available", "name": "Peng Shi", "review_status": "no_course_reviews", "rmp_instructor_id": "rmp:1877077", "summary": [ { "citations": [ { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ], "text": "Recent recorded grades — Fall 2024: 3.53 GPA, 88.2% A/AB (n=17 letter grades); Fall 2025: 3.62 GPA, 71.4% A/AB (n=21 letter grades)." } ] } ] ``` #### difficulty workload None recorded. #### errors None recorded. #### historical context None recorded. #### message No course-specific reviews available #### offered true #### profile hash 672f506f2fc2f46a071b9777f4a92cc197b2ccdeef25590e9285146d8c7e7f90 #### quick take Recent recorded grades — Spring 2025: 3.35 GPA, 70.6% A/AB (n=17 letter grades); Fall 2025: 3.62 GPA, 71.4% A/AB (n=21 letter grades); Spring 2026: 3.65 GPA, 80.0% A/AB (n=30 letter grades). ```json { "citations": [ { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1254", "type": "grade" }, { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" }, { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1264", "type": "grade" } ] } ``` #### student experience None recorded. #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history PENG SHI is recorded teaching in Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "ACTSCI 640", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "source_record": { "entity_id": "a0513339-00cf-33d4-b56e-809eda16ff6d", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ] } ``` #### term id 1272 #### term name 2026 Fall #### version 2 ### requirements #### nodes ```json [ { "children": [ "n1", "n8", "n9" ], "condition": null, "course": null, "evidence": "(GEN BUS 317,ECON 410,STAT/MATH 310,STAT 312,333, or340), graduate/professional standing, or declared in Capstone Certificate in Actuarial Science", "id": "n0", "kind": "any" }, { "children": [ "n2", "n3", "n4", "n5", "n6", "n7" ], "condition": null, "course": null, "evidence": "(GEN BUS 317,ECON 410,STAT/MATH 310,STAT 312,333, or340)", "id": "n1", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 317, "minimum_grade": null, "subjects": [ "GENBUS" ], "timing": "prior" }, "evidence": "GEN BUS 317", "id": "n2", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 410, "minimum_grade": null, "subjects": [ "ECON" ], "timing": "prior" }, "evidence": "ECON 410", "id": "n3", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 310, "minimum_grade": null, "subjects": [ "MATH", "STAT" ], "timing": "prior" }, "evidence": "STAT/MATH 310", "id": "n4", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 312, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "STAT 312", "id": "n5", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 333, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "333", "id": "n6", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 340, "minimum_grade": null, "subjects": [ "STAT" ], "timing": "prior" }, "evidence": "340", "id": "n7", "kind": "course" }, { "children": [], "condition": "graduate/professional standing", "course": null, "evidence": "graduate/professional standing", "id": "n8", "kind": "condition" }, { "children": [], "condition": "declared in Capstone Certificate in Actuarial Science", "course": null, "evidence": "declared in Capstone Certificate in Actuarial Science", "id": "n9", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors ```json [ { "instructor_uid": "instructor_897686e4d69a5b75903adc7a", "source": "enrollment", "source_instructor_id": "pshi", "identity_basis": "netid", "identity_status": "source_identified", "name": "Peng Shi", "email": "PSHI@BUS.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", "ratings": { "review_count": 3, "quality": 4.33, "difficulty": 2.33, "quality_count": 3, "difficulty_count": 3, "profile_id": "rmp:1877077", "source_url": "https://www.ratemyprofessors.com/professor/1877077", "match_basis": "exact_name", "observed_at": "2026-09-07 16:12:10.449164+00:00", "courses": { "course_874e30b1d4fa32884aa74250": { "review_count": 2, "quality": 4.5, "difficulty": 2.5, "quality_count": 2, "difficulty_count": 2 }, "course_2df2f7477ed071a49c40488a": { "review_count": 1, "quality": 4, "difficulty": 2, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7471180726492133, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/PENG_SHI" } ] ``` ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:242:026740", "course_id": "ACTSCI 640", "course_uid": "course_09c6ee1bc749ac38c1a7d335", "term_id": "1272", "source_course_id": "026740", "source_subject_id": "242", "title": "Actuarial Statistics for Risk Modeling", "credits_min": 4, "credits_max": 4, "typically_offered": "Not Applicable" } ] ``` ### sections ```json [ { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:29585", "term_id": "1272", "source_section_id": "29585", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 60, "enrolled": 24, "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_5217fc21c238a5fae9262ddf", "source": "madgrades", "source_instructor_id": "3800534", "identity_basis": "source_id", "identity_status": "source_identified", "name": "PENG SHI", "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": 3, "quality": 4.33, "difficulty": 2.33, "quality_count": 3, "difficulty_count": 3, "profile_id": "rmp:1877077", "source_url": "https://www.ratemyprofessors.com/professor/1877077", "match_basis": "exact_name", "observed_at": "2026-09-07 16:12:10.449164+00:00", "courses": { "course_874e30b1d4fa32884aa74250": { "review_count": 2, "quality": 4.5, "difficulty": 2.5, "quality_count": 2, "difficulty_count": 2 }, "course_2df2f7477ed071a49c40488a": { "review_count": 1, "quality": 4, "difficulty": 2, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7471180726492133, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.377, "graded": 999, "counts": [ 344, 322, 173, 115, 28, 8, 9 ], "sections": 56 }, "instructor_url": "/instructors/PENG_SHI--instructor_5217fc21c238a5fae9262ddf" }, { "instructor_uid": "instructor_853754eefd11575fc47740a1", "source": "madgrades", "source_instructor_id": "2600510", "identity_basis": "source_id", "identity_status": "source_identified", "name": "MARJORIE ROSENBERG", "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": 3.245, "graded": 1027, "counts": [ 345, 202, 254, 125, 80, 11, 10 ], "sections": 55 }, "instructor_url": "/instructors/MARJORIE_ROSENBERG--instructor_853754eefd11575fc47740a1" }, { "instructor_uid": "instructor_a543224f2b400e44d06c4237", "source": "madgrades", "source_instructor_id": "553148", "identity_basis": "source_id", "identity_status": "source_identified", "name": "PAUL JOHNSON", "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": 15, "quality": 3.8, "difficulty": 3.67, "quality_count": 15, "difficulty_count": 15, "profile_id": "rmp:2067033", "source_url": "https://www.ratemyprofessors.com/professor/2067033", "match_basis": "exact_name", "observed_at": "2026-09-07 16:12:31.391967+00:00", "courses": { "course_d5c3b831cc97e1d5bef0f5ff": { "review_count": 1, "quality": 4, "difficulty": 1, "quality_count": 1, "difficulty_count": 1 }, "course_201b25ecc8a2ddee30b320c8": { "review_count": 3, "quality": 4, "difficulty": 3.67, "quality_count": 3, "difficulty_count": 3 }, "course_9f3d31814669db24532fa2c2": { "review_count": 8, "quality": 3.75, "difficulty": 4.12, "quality_count": 8, "difficulty_count": 8 }, "course_969e3f1b5c6d33d8965c5c9b": { "review_count": 1, "quality": 3, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 }, "course_cf57ee176273b438b9f1adc9": { "review_count": 2, "quality": 4, "difficulty": 3, "quality_count": 2, "difficulty_count": 2 } }, "bayesian_quality": 3.719820447740912, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.191, "graded": 1670, "counts": [ 498, 341, 485, 158, 130, 34, 24 ], "sections": 61 }, "instructor_url": "/instructors/PAUL_JOHNSON--instructor_a543224f2b400e44d06c4237" }, { "instructor_uid": "instructor_897686e4d69a5b75903adc7a", "source": "enrollment", "source_instructor_id": "pshi", "identity_basis": "netid", "identity_status": "source_identified", "name": "Peng Shi", "email": "PSHI@BUS.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", "ratings": { "review_count": 3, "quality": 4.33, "difficulty": 2.33, "quality_count": 3, "difficulty_count": 3, "profile_id": "rmp:1877077", "source_url": "https://www.ratemyprofessors.com/professor/1877077", "match_basis": "exact_name", "observed_at": "2026-09-07 16:12:10.449164+00:00", "courses": { "course_874e30b1d4fa32884aa74250": { "review_count": 2, "quality": 4.5, "difficulty": 2.5, "quality_count": 2, "difficulty_count": 2 }, "course_2df2f7477ed071a49c40488a": { "review_count": 1, "quality": 4, "difficulty": 2, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7471180726492133, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/PENG_SHI" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ACTSCI 640", "course_uid": "course_09c6ee1bc749ac38c1a7d335", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Peng Shi" ], "a": 4, "ab": 11, "b": 1, "bc": 1, "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": 17, "source_aliases": [ "ACTSCI 640" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ACTSCI 640", "course_uid": "course_09c6ee1bc749ac38c1a7d335", "term_id": "1254", "term_name": "Spring 2025", "instructors": [ "Margie Rosenberg" ], "a": 6, "ab": 6, "b": 2, "bc": 0, "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": 17, "source_aliases": [ "ACTSCI 640" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ACTSCI 640", "course_uid": "course_09c6ee1bc749ac38c1a7d335", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Peng Shi" ], "a": 11, "ab": 4, "b": 6, "bc": 0, "c": 0, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 21, "source_aliases": [ "ACTSCI 640" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "ACTSCI 640", "course_uid": "course_09c6ee1bc749ac38c1a7d335", "term_id": "1264", "term_name": "Spring 2026", "instructors": [ "Paul Johnson" ], "a": 18, "ab": 6, "b": 4, "bc": 1, "c": 1, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 30, "source_aliases": [ "ACTSCI 640" ] } ] ``` ### statistics #### gpa 3.559 #### graded 85 #### counts * 39 * 27 * 13 * 2 * 4 * 0 * 0 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_09c6ee1bc749ac38c1a7d335-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_09c6ee1bc749ac38c1a7d335-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_09c6ee1bc749ac38c1a7d335-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_09c6ee1bc749ac38c1a7d335-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_09c6ee1bc749ac38c1a7d335-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_09c6ee1bc749ac38c1a7d335-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_09c6ee1bc749ac38c1a7d335-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_09c6ee1bc749ac38c1a7d335-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.5588235294117645 #### count 85 #### university ##### size 3197 ##### gpa Percentile 28 ##### count Percentile 51 ##### median Count 84 ##### 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 | 186 | false | | 3.2–3.6 | 823 | true | | 3.6–4.0 | 2174 | false | #### departments | subject | comparison | | ------- | ---------- | | ACTSCI | | ### terms #### 1252 ##### term 1252 ##### gpa 3.5294117647058822 ##### count 17 ##### departments | subject | comparison | | ------- | ---------- | | ACTSCI | | #### 1254 ##### term 1254 ##### gpa 3.3529411764705883 ##### count 17 ##### departments | subject | comparison | | ------- | ---------- | | ACTSCI | | #### 1262 ##### term 1262 ##### gpa 3.619047619047619 ##### count 21 ##### departments | subject | comparison | | ------- | ---------- | | ACTSCI | | #### 1264 ##### term 1264 ##### gpa 3.65 ##### count 30 ##### university ###### size 1283 ###### gpa Percentile 44 ###### count Percentile 0 ###### 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 | false | | 3.2–3.6 | 343 | false | | 3.6–4.0 | 789 | true | ##### departments | subject | comparison | | ------- | ---------- | | ACTSCI | | ### benchmarks #### all ##### school ###### size 3197 ###### gpa 3.6857992704833213 ###### top Share 83.60953881467515 ###### count 84 #### terms ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ##### 1254 ###### school ###### size 1289 ###### gpa 3.6126423469389106 ###### top Share 79.48050408754871 ###### count 66 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ##### 1264 ###### school ###### size 1283 ###### gpa 3.6229729166451925 ###### top Share 80.13669149396227 ###### count 66 ## instructor Trends ```json [ { "uid": "instructor_5217fc21c238a5fae9262ddf", "name": "PENG SHI", "count": 38, "terms": [ { "term": "1252", "count": 17, "sections": 1, "gpa": 3.5294117647058822 }, { "term": "1262", "count": 21, "sections": 1, "gpa": 3.619047619047619 } ] }, { "uid": "instructor_a543224f2b400e44d06c4237", "name": "PAUL JOHNSON", "count": 30, "terms": [ { "term": "1264", "count": 30, "sections": 1, "gpa": 3.65 } ] }, { "uid": "instructor_853754eefd11575fc47740a1", "name": "MARJORIE ROSENBERG", "count": 17, "terms": [ { "term": "1254", "count": 17, "sections": 1, "gpa": 3.3529411764705883 } ] } ] ``` ## following | code | title | | ---------- | -------------------------------------------------------------------------- | | ACTSCI 654 | REGRESSION AND TIME SERIES FOR ACTUARIES | | ACTSCI 655 | HEALTH ANALYTICS | | ACTSCI 657 | RISK ANALYTICS | | GENBUS 657 | MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE MODELS FOR BUSINESS ANALYTICS | | STAT 441 | ADVANCED SPORTS ANALYTICS |