| Term | Evaluations | Course rating | Instructor rating |
|---|---|---|---|
| Spring 2025 | 2 | 3.0 | 2.5 |
| Fall 2024 | 2 | 3.8 | 3.6 |
| Spring 2024 | 2 | 3.9 | 3.9 |
| Fall 2023 | 2 | 2.8 | 2.5 |
| Spring 2023 | 2 | 2.7 | 2.4 |
| Fall 2022 | 2 | 3.9 | 4.1 |
| Spring 2022 | 2 | 4.2 | 4.4 |
| Fall 2021 | 2 | 3.7 | 3.7 |
| Spring 2021 | 2 | 3.7 | 3.7 |
10 evaluations for this course
This course provides a general introduction to modern probability theory. Topics include probability spaces, discrete and continuous random variables, joint and conditional distributions, mathematical expectation, the central limit theorem, and the weak law of large numbers. Applications to real data will be stressed, and we will use the computer to explore many concepts.
Estimated from the original workload response buckets. Individual sections may differ.
| Fall 2020 | 2 | 3.3 | 3.5 |
| Spring 2020 | 2 | 3.6 | 3.7 |
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