STAT4600
INTERMED STATS MODEL ANALYTICS
Also listed under 1 other title
- BIG DATA STATISTICS I
- Department
- Statistics
- Terms offered
- 14
- Data refreshed
- Jun 30, 2026
Description
Intermediary Statistical Modeling for Analytics emphasizes understanding descriptive, diagnostic, and predictive analytics to identify critical aspects of a business question, from data collection to the formulation and testing of hypotheses. As such, this course is essentially a data science course emphasizing statistical methodologies. At the same time, the course emphasizes the practical aspects of business analytics by embedding the methodologies in applications and underlining the general objective of improving the speed, reliability, and quality of decisions. Topics covered include sampling, inferential statistics, and linear regression. The course uses real-life datasets as illustrations and R to build answers to business questions.
Syllabi
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Offering history & forecast 2017–2025
2017 2025
| Year | Fall | Spring | Summer | Intersession |
|---|---|---|---|---|
| 2030 | 2030 Fall: 39% chance, medium confidence. Offered in 8 of 9 fall terms since 2018. Department course count falling about 20% per year. Department faculty is about 29% below its recent average. | 2030 Spring: 33% chance, medium confidence. Offered in 5 of 6 spring terms since 2021. Department course count falling about 6% per year. Department faculty is about 19% below its recent average. | 2030 Summer: 7% chance, medium confidence. Offered in 0 of 9 summer terms since 2018. | 2030 Intersession: 8% chance, medium confidence. Offered in 0 of 6 intersession terms since 2020. |
| 2029 | 2029 Fall: 43% chance, medium confidence. Offered in 9 of 10 fall terms since 2017. Department course count falling about 18% per year. Department faculty is about 29% below its recent average. | 2029 Spring: 36% chance, medium confidence. Offered in 5 of 6 spring terms since 2021. Department course count falling about 5% per year. Department faculty is about 18% below its recent average. | 2029 Summer: 6% chance, medium confidence. Offered in 0 of 10 summer terms since 2017. | 2029 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017. |
| 2028 | 2028 Fall: 45% chance, medium confidence. Offered in 9 of 10 fall terms since 2017. Section count rising about 1% per year over 2 terms. Department course count falling about 12% per year. Department faculty is about 25% below its recent average. | 2028 Spring: 45% chance, medium confidence. Offered in 5 of 6 spring terms since 2021. Section count rising about 1% per year over 2 terms. Department faculty is about 17% below its recent average. | 2028 Summer: 5% chance, medium confidence. Offered in 0 of 11 summer terms since 2016. | 2028 Intersession: 7% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017. |
| 2027 | 2027 Fall: 48% chance, medium confidence. Offered in 9 of 10 fall terms since 2017. Section count rising about 1% per year over 3 terms. Department course count falling about 9% per year. Department faculty is about 23% below its recent average. | 2027 Spring: 47% chance, medium confidence. Offered in 5 of 6 spring terms since 2021. Section count rising about 1% per year over 3 terms. Department faculty is about 16% below its recent average. | 2027 Summer: 5% chance, high confidence. Offered in 0 of 12 summer terms since 2015. | 2027 Intersession: 6% chance, medium confidence. Offered in 0 of 7 intersession terms since 2017. |
| 2025 | 1 section | 1 section | Not offered | Not offered |
| 2024 | 2 sections | 2 sections | Not offered | Not offered |
| 2023 | 2 sections | 2 sections | Not offered | Not offered |
| 2022 | 2 sections | 1 section | Not offered | Not offered |
| 2021 | 2 sections | 1 section | Not offered | Not offered |
| 2020 | 1 section | Not offered | Not offered | Not offered |
| 2019 | 1 section | Not offered | Not offered | No data for this term |
| 2018 | 1 section | Not offered | Not offered | No data for this term |
| 2017 | 1 section | Not offered | Not offered | Not offered |
Forecast Under 15% 15–39% 40–69% 70–89% 90%+ Not enough history
Fall Spring Summer Intersession Darker means more sections Not offered No data for term
Future estimates combine recent offering frequency with detected multi-year cycles. Hover a cell for confidence and evidence; low-confidence estimates are marked with ~.
Meeting times
Most recent first- Wed, 9:00 AM–11:50 AM JC101 2025
- Mon, 9:00 AM–11:50 AM Carlson Hall CH128 2025
- Thu, 1:25 PM–4:25 PM Sackler Science Center S120 2019
| Term | Professor | Type | Credits | Enrollment | CRN |
|---|---|---|---|---|---|
| Fall 2025 | Yue Gao (She/Her) | Lecture | 1 | 19 of 30 enrolled | 20743 |
| Spring 2025 | Jin Fang | Lecture | 1 | 25 of 30 enrolled | 31277 |
| Fall 2024 | Jin Fang | Lecture | 1 | 19 of 25 enrolled | 20743 |
| Fall 2024 | Jin Fang | Lecture | 1 | 17 of 25 enrolled | 22748 |
| Spring 2024 | Jin Fang | Lecture | 1 | 15 of 20 enrolled | 31277 |
| Spring 2024 | Jin Fang | Lecture | 1 | 7 of 20 enrolled | 32594 |
| Fall 2023 | Yue Gao (She/Her) | Lecture | 1 | 29 of 32 enrolled | 20743 |
| Fall 2023 | Hari C. Krishna | Lecture | 1 | 32 of 42 enrolled | 22748 |
| Spring 2023 | Jin Fang | Lecture | 1 | 9 of 32 enrolled | 31277 |
| Spring 2023 | Jin Fang | Lecture | 1 | 19 of 32 enrolled | 32594 |
| Fall 2022 | Jin Fang | Lecture | 1 | 19 of 30 enrolled | 20743 |
| Fall 2022 | Jin Fang | Lecture | 1 | 18 of 30 enrolled | 21363 |
| Spring 2022 | Jin Fang | Lecture | 1 | 29 of 32 enrolled | 31277 |
| Fall 2021 | Jin Fang | Lecture | 1 | 28 of 30 enrolled | 26251 |
| Fall 2021 | Jin Fang | Lecture | 1 | 10 of 30 enrolled | 28562 |
| Spring 2021 | Theyab Alhwiti | Online | 1 | 14 of 30 enrolled | 38661 |
| Fall 2020 | Theyab Alhwiti | Online | 1 | 17 of 40 enrolled | 26251 |
| Fall 2019 | Haitao Liu | Lecture | 1 | 62 of 50 enrolled | 26251 |
| Fall 2018 | Pankush Kalgotra | Lecture | 1 | 11 of 30 enrolled | 26251 |
| Fall 2017 | Pankush Kalgotra | Lecture | 1 | 11 of 25 enrolled | 26251 |