# BMI/POPHLTH 651: Advanced Regression Methods for Population Health | UW–Madison

[View on UW Courses](https://uwcourses.com/courses/BMI_POPHLTH_651)

## Dataset

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

### repository

twangodev/uwcourses

### schema version

6

### importer version

7

### projection id

94468b7d4154126ca413937bb4738a6d21e0c2277f6fa397a6078ad80a32384f

### observed at

2026-09-07T15:55:43.033547+00:00

### built at

2026-09-10T23:19:01.870283+00:00

### courses

8951

### current instructors

5754

### limited

false

### terms

* 1272
* 1264
* 1262
* 1254
* 1252
* 1244
* 1242
* 1234
* 1232
* 1224
* 1222
* 1212
* 1204
* 1202
* 1194
* 1192
* 1184
* 1182
* 1174
* 1172
* 1164
* 1162
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* 1152
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* 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

3f52d72978af96f4a2a2bd7ae97b099d1ee609fea25d646e5beee3e5aedfc4cd

### course id

BMI/POPHLTH 651

### course uid

course\_a08aa529ddd844ebf5d43f6b

### catalog version id

d92ba542fa2453099bbeb9189d33573cfcbf53bcfe648d9bf514b2e785b067e7

### course number

651

### subjects

* BMI
* POPHLTH

### title

ADVANCED REGRESSION METHODS FOR POPULATION HEALTH

### description

Extension of regression analysis to observational data with unequal variance, unequal sampling and propensity weights, clusters and longitudinal measurements, using different variance structures, mixed linear models, generalized linear models and GEE.  Matrix notation will be introduced and underlying mathematical and statistical principles will be explained.  Examples use data sets from ongoing population health research.

### requirements text

POP HLTH/​B M I  552

### credit offering ids

None recorded.

### llm job id

enrich-8b774950c2b6adfdc46d1b82

### llm output id

77b8add98aa6bef81604d854565b04fabf905f1d66fa8335bead890c92ae555d

### llm model

nvidia/Qwen3.6-35B-A3B-NVFP4

### llm model revision

1355db6a052410cfd62085d94b58866fd0f2c3c5

### llm task version

14

### llm search status

valid

### llm summary

Advanced regression methods for population health, extending analysis to complex observational data structures using mixed models and GEE.

### llm topics

* Propensity weights, clustering, and longitudinal measurements
* Mixed linear models, generalized linear models, and GEE
* Matrix notation and statistical principles

### llm skills

* Advanced regression analysis for complex observational data
* Application of mixed linear models, GLMs, and GEE
* Mathematical and statistical principles using matrix notation

### llm assumed background

* Foundational regression methods for various outcome types

### llm search phrases

* advanced regression population health
* mixed linear models GEE BMI
* propensity weights longitudinal data BMI 651

### llm requirements status

valid

### llm student summary status

valid

### llm experience status

insufficient\_evidence

### catalog variants

None recorded.

### student summary

#### context hash

604f1ae0349860f81489400b4547b307a05b609f90e8b0b9a3725b8a6955167c

#### course id

BMI/POPHLTH 651

#### current instructors

None recorded.

#### difficulty workload

None recorded.

#### errors

None recorded.

#### historical context

None recorded.

#### message

No course-specific reviews available

#### offered

false

#### profile hash

5cb4dabf887cdbcd8c00d5a1312e10828b95c63f30bc3ea76aea199565390d02

#### quick take

Recent recorded grades — Fall 2021: 3.35 GPA, 50.0% A/AB (n=10 letter grades); Fall 2024: 3.65 GPA, 90.0% A/AB (n=10 letter grades); Fall 2025: 3.66 GPA, 87.5% A/AB (n=16 letter grades).

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```

#### student experience

None recorded.

#### task hash

74fb0997943e888960bbc9e47db8c4fd12e4292d55c20509d8d89db6a9910f68

#### teaching history

None recorded.

#### term id

1272

#### term name

2026 Fall

#### version

2

### requirements

#### nodes

```json
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  {
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    "evidence": "POP HLTH/B M I 552",
    "id": "n0",
    "kind": "course"
  }
]
```

#### notes

None recorded.

#### root

n0

#### status

parsed

### instructors

None recorded.

### offerings

None recorded.

### sections

None recorded.

### grade instructors

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```

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    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "BMI/POPHLTH 651",
    "course_uid": "course_a08aa529ddd844ebf5d43f6b",
    "term_id": "1202",
    "term_name": "Fall 2019",
    "instructors": [
      "EMMANUEL SAMPENE"
    ],
    "a": 7,
    "ab": 3,
    "b": 1,
    "bc": 0,
    "c": 0,
    "d": 0,
    "f": 0,
    "satisfactory": 1,
    "unsatisfactory": 0,
    "credit": 0,
    "no_credit": 0,
    "passed": 0,
    "incomplete": 0,
    "no_work": 0,
    "not_reported": 0,
    "other": 0,
    "total": 12,
    "source_aliases": [
      "BMI/POPHLTH 651"
    ]
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "BMI/POPHLTH 651",
    "course_uid": "course_a08aa529ddd844ebf5d43f6b",
    "term_id": "1212",
    "term_name": "Fall 2020",
    "instructors": [
      "EMMANUEL SAMPENE"
    ],
    "a": 3,
    "ab": 4,
    "b": 2,
    "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": 9,
    "source_aliases": [
      "BMI/POPHLTH 651"
    ]
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "BMI/POPHLTH 651",
    "course_uid": "course_a08aa529ddd844ebf5d43f6b",
    "term_id": "1222",
    "term_name": "Fall 2021",
    "instructors": [
      "EMMANUEL SAMPENE"
    ],
    "a": 2,
    "ab": 3,
    "b": 5,
    "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": 10,
    "source_aliases": [
      "BMI/POPHLTH 651"
    ]
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "BMI/POPHLTH 651",
    "course_uid": "course_a08aa529ddd844ebf5d43f6b",
    "term_id": "1234",
    "term_name": "Spring 2023",
    "instructors": [
      "Guanhua Chen"
    ],
    "a": 0,
    "ab": 0,
    "b": 0,
    "bc": 0,
    "c": 0,
    "d": 0,
    "f": 0,
    "satisfactory": 0,
    "unsatisfactory": 0,
    "credit": 0,
    "no_credit": 0,
    "passed": 0,
    "incomplete": 0,
    "no_work": 0,
    "not_reported": 0,
    "other": 0,
    "total": 0,
    "source_aliases": [
      "BMI/POPHLTH 651"
    ]
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "BMI/POPHLTH 651",
    "course_uid": "course_a08aa529ddd844ebf5d43f6b",
    "term_id": "1252",
    "term_name": "Fall 2024",
    "instructors": [
      "MARY RYAN"
    ],
    "a": 4,
    "ab": 5,
    "b": 1,
    "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": 10,
    "source_aliases": [
      "BMI/POPHLTH 651"
    ]
  },
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "course_id": "BMI/POPHLTH 651",
    "course_uid": "course_a08aa529ddd844ebf5d43f6b",
    "term_id": "1262",
    "term_name": "Fall 2025",
    "instructors": [
      "MARY RYAN"
    ],
    "a": 8,
    "ab": 6,
    "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": 16,
    "source_aliases": [
      "BMI/POPHLTH 651"
    ]
  }
]
```

### statistics

#### gpa

3.649

#### graded

121

#### counts

* 59
* 40
* 21
* 1
* 0
* 0
* 0

### grade conflicts

None recorded.

### evidence

#### history

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course\_a08aa529ddd844ebf5d43f6b-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/history/course_a08aa529ddd844ebf5d43f6b-0.json)

#### traces

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course\_a08aa529ddd844ebf5d43f6b-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/traces/course_a08aa529ddd844ebf5d43f6b-0.json)

#### results

* [/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course\_a08aa529ddd844ebf5d43f6b-0.json](https://uwcourses.com/data/e243353dcb7d79b7247ced91d69443ef4c2a6349/results/course_a08aa529ddd844ebf5d43f6b-0.json)

### revision

e243353dcb7d79b7247ced91d69443ef4c2a6349

## context

### all

#### term



#### gpa

3.6487603305785123

#### count

121

#### university

##### size

4174

##### gpa Percentile

42

##### count Percentile

47

##### median Count

130.5

##### histogram

| range   | count | current |
| ------- | ----- | ------- |
| 0.0–0.4 | 0     | false   |
| 0.4–0.8 | 0     | false   |
| 0.8–1.2 | 0     | false   |
| 1.2–1.6 | 0     | false   |
| 1.6–2.0 | 0     | false   |
| 2.0–2.4 | 0     | false   |
| 2.4–2.8 | 13    | false   |
| 2.8–3.2 | 307   | false   |
| 3.2–3.6 | 1199  | false   |
| 3.6–4.0 | 2655  | true    |

#### departments

```json
[
  {
    "subject": "BMI",
    "comparison": {
      "size": 21,
      "gpaPercentile": 10,
      "countPercentile": 70,
      "medianCount": 86,
      "histogram": [
        {
          "range": "0.0–0.4",
          "count": 0,
          "current": false
        },
        {
          "range": "0.4–0.8",
          "count": 0,
          "current": false
        },
        {
          "range": "0.8–1.2",
          "count": 0,
          "current": false
        },
        {
          "range": "1.2–1.6",
          "count": 0,
          "current": false
        },
        {
          "range": "1.6–2.0",
          "count": 0,
          "current": false
        },
        {
          "range": "2.0–2.4",
          "count": 0,
          "current": false
        },
        {
          "range": "2.4–2.8",
          "count": 0,
          "current": false
        },
        {
          "range": "2.8–3.2",
          "count": 0,
          "current": false
        },
        {
          "range": "3.2–3.6",
          "count": 2,
          "current": false
        },
        {
          "range": "3.6–4.0",
          "count": 19,
          "current": true
        }
      ]
    }
  },
  {
    "subject": "POPHLTH",
    "comparison": {
      "size": 24,
      "gpaPercentile": 26,
      "countPercentile": 43,
      "medianCount": 155.5,
      "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": 0,
          "current": false
        },
        {
          "range": "3.2–3.6",
          "count": 5,
          "current": false
        },
        {
          "range": "3.6–4.0",
          "count": 19,
          "current": true
        }
      ]
    }
  }
]
```

### terms

#### 1132

##### term

1132

##### gpa

3.5

##### count

14

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1142

##### term

1142

##### gpa

3.6875

##### count

8

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1152

##### term

1152

##### gpa

3.676470588235294

##### count

17

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1162

##### term

1162

##### gpa

3.590909090909091

##### count

11

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1172

##### term

1172

##### gpa

3.888888888888889

##### count

9

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1194

##### term

1194

##### gpa

4

##### count

6

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1202

##### term

1202

##### gpa

3.772727272727273

##### count

11

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1212

##### term

1212

##### gpa

3.5555555555555554

##### count

9

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1222

##### term

1222

##### gpa

3.35

##### count

10

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1252

##### term

1252

##### gpa

3.65

##### count

10

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

#### 1262

##### term

1262

##### gpa

3.65625

##### count

16

##### departments

| subject | comparison |
| ------- | ---------- |
| BMI     |            |
| POPHLTH |            |

### benchmarks

#### all

##### school

###### size

4174

###### gpa

3.657846718434237

###### top Share

81.7333387146061

###### count

130.5

##### BMI

###### size

21

###### gpa

3.7791498896390525

###### top Share

90.06190312143873

###### count

86

##### POPHLTH

###### size

24

###### gpa

3.7681481709902425

###### top Share

87.59820834442353

###### count

155.5

#### terms

##### 1132

###### school

###### size

851

###### gpa

3.391128778809763

###### top Share

64.69509437122704

###### count

66

###### POPHLTH

###### size

10

###### gpa

3.700553572990855

###### top Share

84.19711217980111

###### count

37.5

##### 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

##### 1194

###### school

###### size

1040

###### gpa

3.4906527436719808

###### top Share

71.74728845515045

###### count

67

##### 1202

###### school

###### size

1102

###### gpa

3.5102605987403313

###### top Share

72.78244569053733

###### count

68

##### 1212

###### school

###### size

1111

###### gpa

3.5856416028074487

###### top Share

77.58926748660845

###### count

68

##### 1222

###### school

###### size

1157

###### gpa

3.563052311875811

###### top Share

76.64869058732418

###### count

64

##### 1234

###### school

###### size

1188

###### gpa

3.5799441677552393

###### top Share

77.18256448537606

###### count

65

##### 1252

###### school

###### size

1333

###### gpa

3.619494049739118

###### top Share

79.71442190500672

###### count

69

##### 1262

###### school

###### size

1320

###### gpa

3.628825763035853

###### top Share

80.21118846327654

###### count

70

## instructor Trends

```json
[
  {
    "uid": "instructor_699e2d13baf3573b224b1dfe",
    "name": "MARI PALTA",
    "count": 39,
    "terms": [
      {
        "term": "1132",
        "count": 14,
        "sections": 1,
        "gpa": 3.5
      },
      {
        "term": "1142",
        "count": 8,
        "sections": 1,
        "gpa": 3.6875
      },
      {
        "term": "1152",
        "count": 17,
        "sections": 1,
        "gpa": 3.676470588235294
      }
    ]
  },
  {
    "uid": "instructor_f1a82ea118f66a96b5dcda1e",
    "name": "EMMANUEL SAMPENE",
    "count": 30,
    "terms": [
      {
        "term": "1202",
        "count": 11,
        "sections": 1,
        "gpa": 3.772727272727273
      },
      {
        "term": "1212",
        "count": 9,
        "sections": 1,
        "gpa": 3.5555555555555554
      },
      {
        "term": "1222",
        "count": 10,
        "sections": 1,
        "gpa": 3.35
      }
    ]
  },
  {
    "uid": "instructor_e0ff4b3f1039ce2db137e6f2",
    "name": "MARY RYAN",
    "count": 26,
    "terms": [
      {
        "term": "1252",
        "count": 10,
        "sections": 1,
        "gpa": 3.65
      },
      {
        "term": "1262",
        "count": 16,
        "sections": 1,
        "gpa": 3.65625
      }
    ]
  },
  {
    "uid": "instructor_f20799d95aade158c151479c",
    "name": "YAJUAN SI",
    "count": 20,
    "terms": [
      {
        "term": "1162",
        "count": 11,
        "sections": 1,
        "gpa": 3.590909090909091
      },
      {
        "term": "1172",
        "count": 9,
        "sections": 1,
        "gpa": 3.888888888888889
      }
    ]
  },
  {
    "uid": "instructor_4d778dafa1ee04996dee46e3",
    "name": "LU MAO",
    "count": 6,
    "terms": [
      {
        "term": "1194",
        "count": 6,
        "sections": 1,
        "gpa": 4
      }
    ]
  }
]
```

## following

None recorded.
