# GENETICS/MDGENET 565: Human Genetics | UW–Madison [View on UW Courses](https://uwcourses.com/courses/GENETICS_MDGENET_565) ## 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 d55895ff0127f06c45b6311fe4acd55eaf1825869dd3388b02a5a5f9bc73956a ### course id GENETICS/MDGENET 565 ### course uid course\_3072ef2bc2ee7e4a222f0281 ### catalog version id 89d5d9208a6f347a7325f3f980f1a0bf35bbce7d4dbb87f32ae202ff375c491e ### course number 565 ### subjects * GENETICS * MDGENET ### title HUMAN GENETICS ### description Principles, problems, and methods of modern human genetics. Focuses on how researchers discover the genetics of diseases and how those discoveries are used to improve clinical practice. Surveys aspects of (i) the molecular function of the human genome, (ii) the basic principles of human genetics including statistical genetics, quantitative genetics, and genomic variation in human populations, (iii) the genetics of rare disorders and common diseases, and genomic analysis approaches, including genome-wide association studies and sequencing, and (iv) how genetics are used in medicine and discussions covering ethical considerations of human genomic data. ### requirements text GENETICS 466,468,BIOCORE 587, or graduate/professional standing ### credits min 3 ### credits max 3 ### credit offering ids * 1272:412:012161 * 1272:616:012161 ### llm job id enrich-f516c4d3e82cfe326b4f5f54 ### llm output id 6de808a5bcd89cc855b730fcc91acbc46d962d5aa0e83afb6f64987be42b0c64 ### llm model nvidia/Qwen3.6-35B-A3B-NVFP4 ### llm model revision 1355db6a052410cfd62085d94b58866fd0f2c3c5 ### llm task version 14 ### llm search status valid ### llm summary Covers principles and methods of modern human genetics, focusing on disease discovery and clinical application. ### llm topics * Molecular function of the human genome * Statistical and quantitative genetics * Genetics of rare and common disorders * Genome-wide association studies and sequencing ### llm skills * Translating genetic discoveries to clinical practice * Genomic analysis using GWAS and sequencing * Ethical evaluation of human genomic data ### llm assumed background * Foundational genetics, population genetics, and scientific literature analysis. ### llm search phrases * human genetics clinical practice * statistical genetics quantitative genetics * genomic variation human populations * genome-wide association studies sequencing * ethics human genomic data ### llm requirements status valid ### llm student summary status valid ### llm experience status valid ### catalog variants None recorded. ### student summary #### context hash c1fb03914fca655d963c312c86dbb4a85d2b1cce7fe70a33d7725737074cea35 #### course id GENETICS/MDGENET 565 #### current instructors ```json [ { "instructor_uid": "instructor_2ad18393e0113733e4ad8d4d", "message": null, "name": "Donna Werling", "review_status": "supported", "rmp_instructor_id": "rmp:3061483", "summary": [ { "citations": [ { "instructor_name": "Donna Werling", "review_date": "2024-12-14 19:42:49 +0000 UTC", "review_id": "00fb92ad07f3bdfc7b01161d", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:3061483", "source_review_id": "UmF0aW5nLTQwMjk3Njg4", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "type": "review" } ], "text": "Donna Werling teaches a difficult but interesting human genetics course that reviewers consider a strong choice for depth. The material is engaging, and lectures are posted online after class." }, { "citations": [ { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ], "text": "Recent recorded grades — Fall 2023: 3.32 GPA, 59.6% A/AB (n=52 letter grades); Fall 2024: 3.19 GPA, 46.4% A/AB (n=56 letter grades); Fall 2025: 3.36 GPA, 68.8% A/AB (n=32 letter grades). Includes jointly taught sections." } ] }, { "instructor_uid": "instructor_d31e3f420f5833c77b41085d", "message": "No course-specific reviews available", "name": "Steven Schrodi", "review_status": "no_course_reviews", "rmp_instructor_id": null, "summary": [ { "citations": [ { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ], "text": "Recent recorded grades — Fall 2023: 3.32 GPA, 59.6% A/AB (n=52 letter grades); Fall 2024: 3.19 GPA, 46.4% A/AB (n=56 letter grades); Fall 2025: 3.36 GPA, 68.8% A/AB (n=32 letter grades). Includes jointly taught sections." } ] } ] ``` #### difficulty workload The material is difficult, and grades are primarily based on three exams and two papers. ```json { "citations": [ { "instructor_name": "Donna Werling", "review_date": "2024-12-14 19:42:49 +0000 UTC", "review_id": "00fb92ad07f3bdfc7b01161d", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:3061483", "source_review_id": "UmF0aW5nLTQwMjk3Njg4", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "type": "review" } ] } ``` #### errors None recorded. #### historical context Historical reviews of Jerry Yin: Jerry Yin is described as an amazing scientist but a disorganized lecturer who struggles to convey concepts clearly. Reviews highlight a disconnect between his emphasis on general concepts and exam questions that test specific details or material not covered in class. ```json { "citations": [ { "instructor_name": "Jerry Yin", "review_date": "2014-01-23 15:41:00 +0000 UTC", "review_id": "5a5d97b613daca239fa8e28d", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1876911", "source_review_id": "UmF0aW5nLTIyNzg2MzY2", "source_url": "https://www.ratemyprofessors.com/professor/1876911", "type": "review" }, { "instructor_name": "Jerry Yin", "review_date": "2018-11-06 14:44:54 +0000 UTC", "review_id": "fac4ff7905f19b15a678dfe2", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1876911", "source_review_id": "UmF0aW5nLTMwNjY5Mjcz", "source_url": "https://www.ratemyprofessors.com/professor/1876911", "type": "review" }, { "instructor_name": "Jerry Yin", "review_date": "2018-11-28 20:42:15 +0000 UTC", "review_id": "bfe975646b857ec4798ee669", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1876911", "source_review_id": "UmF0aW5nLTMwODA4MDkx", "source_url": "https://www.ratemyprofessors.com/professor/1876911", "type": "review" }, { "instructor_name": "Jerry Yin", "review_date": "2019-11-05 03:38:03 +0000 UTC", "review_id": "afcce8879735d9a9ab49abec", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:1876911", "source_review_id": "UmF0aW5nLTMyMzU4Mzkw", "source_url": "https://www.ratemyprofessors.com/professor/1876911", "type": "review" } ] } ``` #### offered true #### profile hash e59ddc7389015d0035b68cd195c939d475bf72b959b29cf12eab59b454ccaef1 #### quick take Reviewers found the course interesting and difficult, recommending it as a strong genetics depth class with current instructors Donna Werling and Steven Schrodi. ```json { "citations": [ { "instructor_name": "Donna Werling", "review_date": "2024-12-14 19:42:49 +0000 UTC", "review_id": "00fb92ad07f3bdfc7b01161d", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:3061483", "source_review_id": "UmF0aW5nLTQwMjk3Njg4", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "type": "review" } ] } ``` Recent recorded grades — Fall 2023: 3.32 GPA, 59.6% A/AB (n=52 letter grades); Fall 2024: 3.19 GPA, 46.4% A/AB (n=56 letter grades); Fall 2025: 3.36 GPA, 68.8% A/AB (n=32 letter grades). ```json { "citations": [ { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "grades_latest", "term_id": "1262", "type": "grade" } ] } ``` #### student experience Lectures are posted online after class, and the content is considered highly interesting by students. ```json { "citations": [ { "instructor_name": "Donna Werling", "review_date": "2024-12-14 19:42:49 +0000 UTC", "review_id": "00fb92ad07f3bdfc7b01161d", "run_id": "20260907T155543-ce3781c4", "source_instructor_id": "rmp:3061483", "source_review_id": "UmF0aW5nLTQwMjk3Njg4", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "type": "review" } ] } ``` #### task hash 74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68 #### teaching history DONNA WERLING is recorded teaching in Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1262", "type": "grade" } ] } ``` JERRY YIN is recorded teaching in Fall 2010, Fall 2011, Fall 2012, Fall 2013, Fall 2014, Fall 2015, Fall 2016, Fall 2017, Fall 2018, Fall 2019. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1112", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1122", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1132", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1142", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1152", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1162", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1172", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1182", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1192", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1202", "type": "grade" } ] } ``` STEVEN SCHRODI is recorded teaching in Fall 2020, Fall 2021, Fall 2022, Fall 2023, Fall 2024, Fall 2025. Recorded history may be incomplete and does not establish a future schedule. ```json { "citations": [ { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1212", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1222", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1232", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1242", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "file": "tables/observations.parquet", "kind": "grades", "source": "madgrades" }, "table": "section_grades_latest", "term_id": "1252", "type": "grade" }, { "course_id": "GENETICS/MDGENET 565", "run_id": "20260907T155543-ce3781c4", "section_number": 1, "source_course_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "source_record": { "entity_id": "9c62ead3-8598-3a7d-852b-e548883ea340", "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", "n2", "n3", "n4" ], "condition": null, "course": null, "evidence": "GENETICS 466,468,BIOCORE 587, or graduate/professional standing", "id": "n0", "kind": "any" }, { "children": [], "condition": null, "course": { "course_number": 466, "minimum_grade": null, "subjects": [ "GENETICS" ], "timing": "prior" }, "evidence": "GENETICS 466", "id": "n1", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 468, "minimum_grade": null, "subjects": [ "GENETICS" ], "timing": "prior" }, "evidence": "468", "id": "n2", "kind": "course" }, { "children": [], "condition": null, "course": { "course_number": 587, "minimum_grade": null, "subjects": [ "BIOCORE" ], "timing": "prior" }, "evidence": "BIOCORE 587", "id": "n3", "kind": "course" }, { "children": [], "condition": "graduate/professional standing", "course": null, "evidence": "graduate/professional standing", "id": "n4", "kind": "condition" } ] ``` #### notes None recorded. #### root n0 #### status parsed ### instructors ```json [ { "instructor_uid": "instructor_2ad18393e0113733e4ad8d4d", "source": "enrollment", "source_instructor_id": "dwerling", "identity_basis": "netid", "identity_status": "source_identified", "name": "Donna Werling", "email": "DWERLING@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": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1, "profile_id": "rmp:3061483", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "match_basis": "exact_name", "observed_at": "2026-09-07 16:43:16.727715+00:00", "courses": { "course_3072ef2bc2ee7e4a222f0281": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7235102700443767, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/DONNA_WERLING" }, { "instructor_uid": "instructor_d31e3f420f5833c77b41085d", "source": "enrollment", "source_instructor_id": "schrodi", "identity_basis": "netid", "identity_status": "source_identified", "name": "Steven Schrodi", "email": "SCHRODI@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/STEVEN_SCHRODI" } ] ``` ### offerings ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:412:012161", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1272", "source_course_id": "012161", "source_subject_id": "412", "title": "Human Genetics", "credits_min": 3, "credits_max": 3, "typically_offered": "Fall" }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "offering_id": "1272:616:012161", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1272", "source_course_id": "012161", "source_subject_id": "616", "title": "Human Genetics", "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:1272:10103", "term_id": "1272", "source_section_id": "10103", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 60, "enrolled": 38, "waitlisted": 0, "start_date": "2026-09-02 05:00:00+00:00", "end_date": "2026-12-09 06:00:00+00:00" }, { "run_id": "20260907T155543-ce3781c4", "observed_at": "2026-09-07 15:55:43.033547+00:00", "section_uid": "uw-section:1272:16668", "term_id": "1272", "source_section_id": "16668", "identity_basis": "class_number", "section_number": "001", "section_type": "LEC", "instruction_mode": "Classroom Instruction", "capacity": 0, "enrolled": 0, "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_08d7424e4d7d919ef2d95711", "source": "madgrades", "source_instructor_id": "4004467", "identity_basis": "source_id", "identity_status": "source_identified", "name": "BRET PAYSEUR", "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": 4.18, "difficulty": 2.55, "quality_count": 11, "difficulty_count": 11, "profile_id": "rmp:1662159", "source_url": "https://www.ratemyprofessors.com/professor/1662159", "match_basis": "exact_name", "observed_at": "2026-09-07 16:51:20.506134+00:00", "courses": { "course_bbfd76ac0fb3ee00a37e7090": { "review_count": 3, "quality": 4, "difficulty": 2.67, "quality_count": 3, "difficulty_count": 3 } }, "bayesian_quality": 3.8443134087397386, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.057, "graded": 1106, "counts": [ 298, 240, 233, 123, 143, 57, 12 ], "sections": 127 }, "instructor_url": "/instructors/BRET_PAYSEUR--instructor_08d7424e4d7d919ef2d95711" }, { "instructor_uid": "instructor_9e820bad7c45a5eae810e11f", "source": "madgrades", "source_instructor_id": "2601956", "identity_basis": "source_id", "identity_status": "source_identified", "name": "TOMAS PROLLA", "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": 3.362, "graded": 598, "counts": [ 264, 121, 108, 36, 50, 17, 2 ], "sections": 30 }, "instructor_url": "/instructors/TOMAS_PROLLA--instructor_9e820bad7c45a5eae810e11f" }, { "instructor_uid": "instructor_4f395b5afc3350fdf66d0dbf", "source": "madgrades", "source_instructor_id": "164989", "identity_basis": "source_id", "identity_status": "source_identified", "name": "JERRY YIN", "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": 7, "quality": 3.14, "difficulty": 3.57, "quality_count": 7, "difficulty_count": 7, "profile_id": "rmp:1876911", "source_url": "https://www.ratemyprofessors.com/professor/1876911", "match_basis": "exact_name", "observed_at": "2026-09-07 16:32:59.519619+00:00", "courses": { "course_3072ef2bc2ee7e4a222f0281": { "review_count": 4, "quality": 3, "difficulty": 3.5, "quality_count": 4, "difficulty_count": 4 } }, "bayesian_quality": 3.5249524322567374, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.307, "graded": 1001, "counts": [ 310, 234, 285, 110, 60, 1, 1 ], "sections": 120 }, "instructor_url": "/instructors/JERRY_YIN--instructor_4f395b5afc3350fdf66d0dbf" }, { "instructor_uid": "instructor_7554efc780320d1253a3614c", "source": "madgrades", "source_instructor_id": "3800766", "identity_basis": "source_id", "identity_status": "source_identified", "name": "AKIHIRO IKEDA", "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": 1, "quality": 5, "difficulty": 3, "quality_count": 1, "difficulty_count": 1, "profile_id": "rmp:2431606", "source_url": "https://www.ratemyprofessors.com/professor/2431606", "match_basis": "exact_name", "observed_at": "2026-09-07 16:57:20.463201+00:00", "courses": {}, "bayesian_quality": 3.7235102700443767, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.29, "graded": 852, "counts": [ 276, 165, 250, 101, 59, 1, 0 ], "sections": 106 }, "instructor_url": "/instructors/AKIHIRO_IKEDA--instructor_7554efc780320d1253a3614c" }, { "instructor_uid": "instructor_86b5107d8dc2410f29d9ac4e", "source": "madgrades", "source_instructor_id": "5000709", "identity_basis": "source_id", "identity_status": "source_identified", "name": "REID ALISCH", "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": 3.125, "graded": 56, "counts": [ 13, 13, 12, 11, 7, 0, 0 ], "sections": 48 }, "instructor_url": "/instructors/REID_ALISCH--instructor_86b5107d8dc2410f29d9ac4e" }, { "instructor_uid": "instructor_464e486df67acbaa6a65c95d", "source": "madgrades", "source_instructor_id": "6240297", "identity_basis": "source_id", "identity_status": "source_identified", "name": "STEVEN SCHRODI", "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": 3.388, "graded": 343, "counts": [ 119, 105, 69, 27, 21, 2, 0 ], "sections": 22 }, "instructor_url": "/instructors/STEVEN_SCHRODI--instructor_464e486df67acbaa6a65c95d" }, { "instructor_uid": "instructor_a65313e1cd0f224501485ce3", "source": "madgrades", "source_instructor_id": "3728293", "identity_basis": "source_id", "identity_status": "source_identified", "name": "DONNA WERLING", "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": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1, "profile_id": "rmp:3061483", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "match_basis": "exact_name", "observed_at": "2026-09-07 16:43:16.727715+00:00", "courses": { "course_3072ef2bc2ee7e4a222f0281": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7235102700443767, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "grade_statistics": { "gpa": 3.412, "graded": 370, "counts": [ 137, 107, 77, 26, 21, 2, 0 ], "sections": 50 }, "instructor_url": "/instructors/DONNA_WERLING--instructor_a65313e1cd0f224501485ce3" }, { "instructor_uid": "instructor_2ad18393e0113733e4ad8d4d", "source": "enrollment", "source_instructor_id": "dwerling", "identity_basis": "netid", "identity_status": "source_identified", "name": "Donna Werling", "email": "DWERLING@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": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1, "profile_id": "rmp:3061483", "source_url": "https://www.ratemyprofessors.com/professor/3061483", "match_basis": "exact_name", "observed_at": "2026-09-07 16:43:16.727715+00:00", "courses": { "course_3072ef2bc2ee7e4a222f0281": { "review_count": 1, "quality": 5, "difficulty": 4, "quality_count": 1, "difficulty_count": 1 } }, "bayesian_quality": 3.7235102700443767, "prior_mean": 3.6596857835465957, "prior_weight": 20 }, "instructor_url": "/instructors/DONNA_WERLING" }, { "instructor_uid": "instructor_d31e3f420f5833c77b41085d", "source": "enrollment", "source_instructor_id": "schrodi", "identity_basis": "netid", "identity_status": "source_identified", "name": "Steven Schrodi", "email": "SCHRODI@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/STEVEN_SCHRODI" } ] ``` ### grades ```json [ { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1072", "term_name": "Fall 2006", "instructors": [ "Bret Payseur", "Tomas Prolla" ], "a": 15, "ab": 0, "b": 18, "bc": 0, "c": 12, "d": 5, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 51, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1082", "term_name": "Fall 2007", "instructors": [ "Bret Payseur", "Tomas Prolla" ], "a": 8, "ab": 9, "b": 7, "bc": 9, "c": 7, "d": 7, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 47, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1092", "term_name": "Fall 2008", "instructors": [ "Bret Payseur", "Tomas Prolla" ], "a": 11, "ab": 9, "b": 9, "bc": 12, "c": 11, "d": 5, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 57, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1102", "term_name": "Fall 2009", "instructors": [ "Bret Payseur", "Tomas Prolla" ], "a": 11, "ab": 7, "b": 10, "bc": 8, "c": 10, "d": 0, "f": 1, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 0, "other": 0, "total": 47, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1112", "term_name": "Fall 2010", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 10, "ab": 11, "b": 18, "bc": 7, "c": 5, "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": 51, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1122", "term_name": "Fall 2011", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 9, "ab": 9, "b": 14, "bc": 11, "c": 1, "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": 45, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1132", "term_name": "Fall 2012", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 10, "ab": 7, "b": 18, "bc": 7, "c": 9, "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": 51, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1142", "term_name": "Fall 2013", "instructors": [ "Jerry Yin" ], "a": 9, "ab": 10, "b": 26, "bc": 6, "c": 5, "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": 56, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1152", "term_name": "Fall 2014", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 12, "ab": 13, "b": 16, "bc": 8, "c": 9, "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": 59, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1162", "term_name": "Fall 2015", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 12, "ab": 14, "b": 25, "bc": 3, "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": 55, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1172", "term_name": "Fall 2016", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 10, "ab": 14, "b": 16, "bc": 13, "c": 5, "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": 58, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1182", "term_name": "Fall 2017", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 12, "ab": 11, "b": 20, "bc": 11, "c": 6, "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": 61, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1192", "term_name": "Fall 2018", "instructors": [ "Akihiro Ikeda", "Jerry Yin" ], "a": 12, "ab": 11, "b": 18, "bc": 8, "c": 8, "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": 57, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1202", "term_name": "Fall 2019", "instructors": [ "Akihiro Ikeda", "Jerry Yin", "Reid Alisch" ], "a": 12, "ab": 13, "b": 12, "bc": 11, "c": 7, "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": 55, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1212", "term_name": "Fall 2020", "instructors": [ "Akihiro Ikeda", "Donna Werling", "Steven Schrodi" ], "a": 29, "ab": 11, "b": 16, "bc": 2, "c": 6, "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": 66, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1222", "term_name": "Fall 2021", "instructors": [ "Donna Werling", "Steven Schrodi" ], "a": 12, "ab": 19, "b": 6, "bc": 3, "c": 3, "d": 0, "f": 0, "satisfactory": 0, "unsatisfactory": 0, "credit": 0, "no_credit": 0, "passed": 0, "incomplete": 0, "no_work": 0, "not_reported": 1, "other": 0, "total": 44, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1232", "term_name": "Fall 2022", "instructors": [ "Donna Werling", "Steven Schrodi" ], "a": 9, "ab": 13, "b": 9, "bc": 6, "c": 1, "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": 40, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1242", "term_name": "Fall 2023", "instructors": [ "Donna Werling", "Steven Schrodi" ], "a": 13, "ab": 18, "b": 13, "bc": 5, "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": 52, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1252", "term_name": "Fall 2024", "instructors": [ "Donna Werling", "Steven Schrodi" ], "a": 10, "ab": 16, "b": 20, "bc": 5, "c": 5, "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": 56, "source_aliases": [ "GENETICS/MDGENET 565" ] }, { "run_id": "20260907T155543-ce3781c4", "semester": "1272", "observed_at": "2026-09-07 15:55:43.033547+00:00", "course_id": "GENETICS/MDGENET 565", "course_uid": "course_3072ef2bc2ee7e4a222f0281", "term_id": "1262", "term_name": "Fall 2025", "instructors": [ "Donna Werling", "Steven Schrodi" ], "a": 12, "ab": 10, "b": 2, "bc": 5, "c": 3, "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": 33, "source_aliases": [ "GENETICS/MDGENET 565" ] } ] ``` ### statistics #### gpa 3.114 #### graded 1035 #### counts * 238 * 225 * 293 * 140 * 117 * 20 * 2 ### grade conflicts None recorded. ### evidence #### history * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_3072ef2bc2ee7e4a222f0281-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_3072ef2bc2ee7e4a222f0281-0.json) #### traces * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_3072ef2bc2ee7e4a222f0281-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_3072ef2bc2ee7e4a222f0281-0.json) #### reviews * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course\_3072ef2bc2ee7e4a222f0281-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/reviews/course_3072ef2bc2ee7e4a222f0281-0.json) #### meetings * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course\_3072ef2bc2ee7e4a222f0281-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/meetings/course_3072ef2bc2ee7e4a222f0281-0.json) #### results * [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_3072ef2bc2ee7e4a222f0281-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_3072ef2bc2ee7e4a222f0281-0.json) ### revision e243353dcb7d79b7247ced91d69443ef4c2a6349 ## context ### all #### term #### gpa 3.1135265700483092 #### count 1035 #### university ##### size 4146 ##### gpa Percentile 5 ##### count Percentile 86 ##### median Count 193 ##### 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 | 10 | false | | 2.8–3.2 | 326 | true | | 3.2–3.6 | 1185 | false | | 3.6–4.0 | 2625 | false | #### departments ```json [ { "subject": "GENETICS", "comparison": { "size": 27, "gpaPercentile": 8, "countPercentile": 88, "medianCount": 201, "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": 2, "current": true }, { "range": "3.2–3.6", "count": 5, "current": false }, { "range": "3.6–4.0", "count": 19, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` ### terms #### 1072 ##### term 1072 ##### gpa 2.803921568627451 ##### count 51 ##### university ###### size 723 ###### gpa Percentile 9 ###### count Percentile 35 ###### 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 | 62 | false | | 2.8–3.2 | 174 | true | | 3.2–3.6 | 306 | false | | 3.6–4.0 | 180 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1082 ##### term 1082 ##### gpa 2.723404255319149 ##### count 47 ##### university ###### size 723 ###### gpa Percentile 4 ###### count Percentile 29 ###### 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 | 51 | true | | 2.8–3.2 | 202 | false | | 3.2–3.6 | 265 | false | | 3.6–4.0 | 204 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1092 ##### term 1092 ##### gpa 2.7982456140350878 ##### count 57 ##### university ###### size 732 ###### gpa Percentile 5 ###### count Percentile 40 ###### 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 | 41 | true | | 2.8–3.2 | 208 | false | | 3.2–3.6 | 271 | false | | 3.6–4.0 | 211 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1102 ##### term 1102 ##### gpa 2.9468085106382977 ##### count 47 ##### university ###### size 774 ###### gpa Percentile 14 ###### count Percentile 31 ###### 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 | 1 | false | | 2.0–2.4 | 1 | false | | 2.4–2.8 | 49 | false | | 2.8–3.2 | 201 | true | | 3.2–3.6 | 287 | false | | 3.6–4.0 | 235 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1112 ##### term 1112 ##### gpa 3.1372549019607843 ##### count 51 ##### university ###### size 805 ###### gpa Percentile 27 ###### count Percentile 35 ###### 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 | 45 | false | | 2.8–3.2 | 218 | true | | 3.2–3.6 | 316 | false | | 3.6–4.0 | 225 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1122 ##### term 1122 ##### gpa 3.159090909090909 ##### count 44 ##### university ###### size 804 ###### gpa Percentile 30 ###### count Percentile 26 ###### 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 | 3 | false | | 2.4–2.8 | 47 | false | | 2.8–3.2 | 224 | true | | 3.2–3.6 | 282 | false | | 3.6–4.0 | 248 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1132 ##### term 1132 ##### gpa 3.019607843137255 ##### count 51 ##### university ###### size 851 ###### gpa Percentile 16 ###### count Percentile 37 ###### 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 | 40 | false | | 2.8–3.2 | 234 | true | | 3.2–3.6 | 303 | false | | 3.6–4.0 | 272 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1142 ##### term 1142 ##### gpa 3.107142857142857 ##### count 56 ##### university ###### size 853 ###### gpa Percentile 24 ###### count Percentile 41 ###### 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 | 4 | false | | 2.4–2.8 | 33 | false | | 2.8–3.2 | 228 | true | | 3.2–3.6 | 320 | false | | 3.6–4.0 | 268 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1152 ##### term 1152 ##### gpa 3.059322033898305 ##### count 59 ##### university ###### size 918 ###### gpa Percentile 18 ###### count Percentile 44 ###### 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 | 1 | false | | 2.4–2.8 | 33 | false | | 2.8–3.2 | 227 | true | | 3.2–3.6 | 371 | false | | 3.6–4.0 | 286 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1162 ##### term 1162 ##### gpa 3.3 ##### count 55 ##### university ###### size 954 ###### gpa Percentile 35 ###### count Percentile 42 ###### 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 | true | | 3.6–4.0 | 345 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1172 ##### term 1172 ##### gpa 3.0948275862068964 ##### count 58 ##### university ###### size 991 ###### gpa Percentile 17 ###### count Percentile 42 ###### 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 | true | | 3.2–3.6 | 353 | false | | 3.6–4.0 | 390 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1182 ##### term 1182 ##### gpa 3.1 ##### count 60 ##### university ###### size 1025 ###### gpa Percentile 18 ###### count Percentile 42 ###### 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 | true | | 3.2–3.6 | 369 | false | | 3.6–4.0 | 418 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1192 ##### term 1192 ##### gpa 3.0964912280701755 ##### count 57 ##### university ###### size 1077 ###### gpa Percentile 15 ###### count Percentile 41 ###### 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 | true | | 3.2–3.6 | 370 | false | | 3.6–4.0 | 481 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1202 ##### term 1202 ##### gpa 3.109090909090909 ##### count 55 ##### university ###### size 1102 ###### gpa Percentile 15 ###### count Percentile 39 ###### 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 | true | | 3.2–3.6 | 371 | false | | 3.6–4.0 | 498 | false | ##### departments ```json [ { "subject": "GENETICS", "comparison": { "size": 10, "gpaPercentile": 22, "countPercentile": 44, "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": 0, "current": false }, { "range": "2.8–3.2", "count": 3, "current": true }, { "range": "3.2–3.6", "count": 4, "current": false }, { "range": "3.6–4.0", "count": 3, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` #### 1212 ##### term 1212 ##### gpa 3.4296875 ##### count 64 ##### university ###### size 1111 ###### gpa Percentile 29 ###### count Percentile 46 ###### 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": "GENETICS", "comparison": { "size": 10, "gpaPercentile": 22, "countPercentile": 44, "medianCount": 64.5, "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": 4, "current": true }, { "range": "3.6–4.0", "count": 5, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` #### 1222 ##### term 1222 ##### gpa 3.395348837209302 ##### count 43 ##### university ###### size 1157 ###### gpa Percentile 30 ###### count Percentile 27 ###### 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": "GENETICS", "comparison": { "size": 12, "gpaPercentile": 27, "countPercentile": 45, "medianCount": 43.5, "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": 1, "current": false }, { "range": "2.8–3.2", "count": 1, "current": false }, { "range": "3.2–3.6", "count": 3, "current": true }, { "range": "3.6–4.0", "count": 7, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` #### 1232 ##### term 1232 ##### gpa 3.1875 ##### count 40 ##### university ###### size 1216 ###### gpa Percentile 15 ###### count Percentile 21 ###### 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 | true | | 3.2–3.6 | 356 | false | | 3.6–4.0 | 670 | false | ##### departments | subject | comparison | | -------- | ---------- | | GENETICS | | | MDGENET | | #### 1242 ##### term 1242 ##### gpa 3.3173076923076925 ##### count 52 ##### university ###### size 1295 ###### gpa Percentile 21 ###### count Percentile 39 ###### 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 | 2 | false | | 2.4–2.8 | 11 | false | | 2.8–3.2 | 162 | false | | 3.2–3.6 | 394 | true | | 3.6–4.0 | 726 | false | ##### departments ```json [ { "subject": "GENETICS", "comparison": { "size": 12, "gpaPercentile": 18, "countPercentile": 36, "medianCount": 55.5, "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": 1, "current": false }, { "range": "2.8–3.2", "count": 1, "current": false }, { "range": "3.2–3.6", "count": 3, "current": true }, { "range": "3.6–4.0", "count": 7, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` #### 1252 ##### term 1252 ##### gpa 3.1875 ##### count 56 ##### university ###### size 1333 ###### gpa Percentile 9 ###### count Percentile 40 ###### 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 | true | | 3.2–3.6 | 431 | false | | 3.6–4.0 | 773 | false | ##### departments ```json [ { "subject": "GENETICS", "comparison": { "size": 12, "gpaPercentile": 18, "countPercentile": 55, "medianCount": 52.5, "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": 3, "current": true }, { "range": "3.2–3.6", "count": 0, "current": false }, { "range": "3.6–4.0", "count": 9, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` #### 1262 ##### term 1262 ##### gpa 3.359375 ##### count 32 ##### university ###### size 1320 ###### gpa Percentile 19 ###### count Percentile 5 ###### 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": "GENETICS", "comparison": { "size": 13, "gpaPercentile": 17, "countPercentile": 17, "medianCount": 53, "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": 3, "current": true }, { "range": "3.6–4.0", "count": 9, "current": false } ] } }, { "subject": "MDGENET", "comparison": null } ] ``` ### benchmarks #### all ##### school ###### size 4146 ###### gpa 3.655576857310451 ###### top Share 81.61127984016484 ###### count 193 ##### GENETICS ###### size 27 ###### gpa 3.6777183126984423 ###### top Share 82.02352509738994 ###### count 201 #### terms ##### 1072 ###### school ###### size 723 ###### gpa 3.344595727439471 ###### top Share 62.012941427864526 ###### count 67 ##### 1082 ###### school ###### size 723 ###### gpa 3.3583896732335172 ###### top Share 62.932746798940194 ###### count 68 ##### 1092 ###### school ###### size 732 ###### gpa 3.374660709520374 ###### top Share 63.690339324346596 ###### count 70 ##### 1102 ###### school ###### size 774 ###### gpa 3.36712622366007 ###### top Share 63.703228532165696 ###### count 67 ##### 1112 ###### school ###### size 805 ###### gpa 3.3737773184830386 ###### top Share 63.91039244872789 ###### count 66 ##### 1122 ###### school ###### size 804 ###### gpa 3.3737149752667013 ###### top Share 63.65118790117902 ###### count 70 ##### 1132 ###### school ###### size 851 ###### gpa 3.391128778809763 ###### top Share 64.69509437122704 ###### count 66 ##### 1142 ###### school ###### size 853 ###### gpa 3.3941849959684913 ###### top Share 65.28450334228523 ###### count 67 ##### 1152 ###### school ###### size 918 ###### gpa 3.408733538594633 ###### top Share 66.06693005846735 ###### count 65 ##### 1162 ###### school ###### size 954 ###### gpa 3.43726781345039 ###### top Share 68.05645304987395 ###### count 64.5 ##### 1172 ###### school ###### size 991 ###### gpa 3.465129042641772 ###### top Share 69.42600667567366 ###### count 67 ##### 1182 ###### school ###### size 1025 ###### gpa 3.474159360325319 ###### top Share 70.34861441764347 ###### count 69 ##### 1192 ###### school ###### size 1077 ###### gpa 3.50327634323125 ###### top Share 72.44641925727845 ###### count 67 ##### 1202 ###### school ###### size 1102 ###### gpa 3.5102605987403313 ###### top Share 72.78244569053733 ###### count 68 ###### GENETICS ###### size 10 ###### gpa 3.451827575944905 ###### top Share 68.57560463766207 ###### count 55 ##### 1212 ###### school ###### size 1111 ###### gpa 3.5856416028074487 ###### top Share 77.58926748660845 ###### count 68 ###### GENETICS ###### size 10 ###### gpa 3.5728472785775116 ###### top Share 76.39656652328354 ###### count 64.5 ##### 1222 ###### school ###### size 1157 ###### gpa 3.563052311875811 ###### top Share 76.64869058732418 ###### count 64 ###### GENETICS ###### size 12 ###### gpa 3.5487219422313245 ###### top Share 75.54325666174324 ###### count 43.5 ##### 1232 ###### school ###### size 1216 ###### gpa 3.575457431972425 ###### top Share 77.33712216234007 ###### count 66 ##### 1242 ###### school ###### size 1295 ###### gpa 3.595302892737449 ###### top Share 78.36291889885307 ###### count 67 ###### GENETICS ###### size 12 ###### gpa 3.5884554184793362 ###### top Share 77.27523156397659 ###### count 55.5 ##### 1252 ###### school ###### size 1333 ###### gpa 3.619494049739118 ###### top Share 79.71442190500672 ###### count 69 ###### GENETICS ###### size 12 ###### gpa 3.630871422034851 ###### top Share 79.70819282550313 ###### count 52.5 ##### 1262 ###### school ###### size 1320 ###### gpa 3.628825763035853 ###### top Share 80.21118846327654 ###### count 70 ###### GENETICS ###### size 13 ###### gpa 3.698788127912363 ###### top Share 83.51083061370407 ###### count 53 ## instructor Trends ```json [ { "uid": "instructor_7554efc780320d1253a3614c", "name": "AKIHIRO IKEDA", "count": 554, "terms": [ { "term": "1112", "count": 51, "sections": 1, "gpa": 3.1372549019607843 }, { "term": "1122", "count": 44, "sections": 1, "gpa": 3.159090909090909 }, { "term": "1132", "count": 51, "sections": 1, "gpa": 3.019607843137255 }, { "term": "1152", "count": 59, "sections": 1, "gpa": 3.059322033898305 }, { "term": "1162", "count": 55, "sections": 1, "gpa": 3.3 }, { "term": "1172", "count": 58, "sections": 1, "gpa": 3.0948275862068964 }, { "term": "1182", "count": 60, "sections": 1, "gpa": 3.1 }, { "term": "1192", "count": 57, "sections": 1, "gpa": 3.0964912280701755 }, { "term": "1202", "count": 55, "sections": 1, "gpa": 3.109090909090909 }, { "term": "1212", "count": 64, "sections": 1, "gpa": 3.4296875 } ] }, { "uid": "instructor_4f395b5afc3350fdf66d0dbf", "name": "JERRY YIN", "count": 546, "terms": [ { "term": "1112", "count": 51, "sections": 1, "gpa": 3.1372549019607843 }, { "term": "1122", "count": 44, "sections": 1, "gpa": 3.159090909090909 }, { "term": "1132", "count": 51, "sections": 1, "gpa": 3.019607843137255 }, { "term": "1142", "count": 56, "sections": 1, "gpa": 3.107142857142857 }, { "term": "1152", "count": 59, "sections": 1, "gpa": 3.059322033898305 }, { "term": "1162", "count": 55, "sections": 1, "gpa": 3.3 }, { "term": "1172", "count": 58, "sections": 1, "gpa": 3.0948275862068964 }, { "term": "1182", "count": 60, "sections": 1, "gpa": 3.1 }, { "term": "1192", "count": 57, "sections": 1, "gpa": 3.0964912280701755 }, { "term": "1202", "count": 55, "sections": 1, "gpa": 3.109090909090909 } ] }, { "uid": "instructor_464e486df67acbaa6a65c95d", "name": "STEVEN SCHRODI", "count": 287, "terms": [ { "term": "1212", "count": 64, "sections": 1, "gpa": 3.4296875 }, { "term": "1222", "count": 43, "sections": 1, "gpa": 3.395348837209302 }, { "term": "1232", "count": 40, "sections": 1, "gpa": 3.1875 }, { "term": "1242", "count": 52, "sections": 1, "gpa": 3.3173076923076925 }, { "term": "1252", "count": 56, "sections": 1, "gpa": 3.1875 }, { "term": "1262", "count": 32, "sections": 1, "gpa": 3.359375 } ] }, { "uid": "instructor_a65313e1cd0f224501485ce3", "name": "DONNA WERLING", "count": 287, "terms": [ { "term": "1212", "count": 64, "sections": 1, "gpa": 3.4296875 }, { "term": "1222", "count": 43, "sections": 1, "gpa": 3.395348837209302 }, { "term": "1232", "count": 40, "sections": 1, "gpa": 3.1875 }, { "term": "1242", "count": 52, "sections": 1, "gpa": 3.3173076923076925 }, { "term": "1252", "count": 56, "sections": 1, "gpa": 3.1875 }, { "term": "1262", "count": 32, "sections": 1, "gpa": 3.359375 } ] }, { "uid": "instructor_08d7424e4d7d919ef2d95711", "name": "BRET PAYSEUR", "count": 202, "terms": [ { "term": "1072", "count": 51, "sections": 1, "gpa": 2.803921568627451 }, { "term": "1082", "count": 47, "sections": 1, "gpa": 2.723404255319149 }, { "term": "1092", "count": 57, "sections": 1, "gpa": 2.7982456140350878 }, { "term": "1102", "count": 47, "sections": 1, "gpa": 2.9468085106382977 } ] }, { "uid": "instructor_9e820bad7c45a5eae810e11f", "name": "TOMAS PROLLA", "count": 202, "terms": [ { "term": "1072", "count": 51, "sections": 1, "gpa": 2.803921568627451 }, { "term": "1082", "count": 47, "sections": 1, "gpa": 2.723404255319149 }, { "term": "1092", "count": 57, "sections": 1, "gpa": 2.7982456140350878 }, { "term": "1102", "count": 47, "sections": 1, "gpa": 2.9468085106382977 } ] }, { "uid": "instructor_86b5107d8dc2410f29d9ac4e", "name": "REID ALISCH", "count": 55, "terms": [ { "term": "1202", "count": 55, "sections": 1, "gpa": 3.109090909090909 } ] } ] ``` ## following None recorded. ## projection ### target 1272 ### interval #### lower 2.98 #### upper 3.6 #### coverage 80 #### terms 8 ### gpa 3.2886681362440062 ### grades | grade | percentage | | ----- | ------------------ | | A | 26.992031163771085 | | AB | 33.01986960440023 | | B | 20.24535263226971 | | BC | 11.738272761574233 | | C | 7.242931715186068 | | D | 0.7615421227986674 | | F | 0 | ### source Terms * 1262 * 1252 * 1242 * 1232 * 1222 ### source Count 223 ### same Season true ### historical Range * 3.1874999999999996 * 3.395348837209302 ### backtest #### terms 8 #### gpa Error 0.10908480907875029 #### mix Error 15.909249536140269