| Term | Evaluations | Course rating | Instructor rating |
|---|---|---|---|
| Spring 2025 | 1 | 4.2 | 4.3 |
| Fall 2024 | 1 | 4.8 | 4.5 |
| Summer 2024 | 1 | 2.8 | 1.5 |
| Spring 2024 | 1 | 3.7 | 3.7 |
| Spring 2023 | 1 | 3.6 | 4.4 |
| Fall 2022 | 1 | 3.8 | 3.8 |
| Spring 2022 | 1 | 4.3 | 4.6 |
| Spring 2021 | 1 | 3.4 | 4.0 |
This course is designed to provide students with a foundation in statistical analysis and computing. This class focuses on the concepts, language, and application of statistics to social sciences. In particular, students will learn to produce and interpret descriptive statistics and graphical and numerical representation of information; additionally, students will learn about measures of location, dispersion, position, and dependence, and how to conduct exploratory data analysis. Additional topics will include elementary probability theory (to aid with interpretation and understanding), point and interval estimation, hypothesis significance testing, and linear regression. To help facilitate understanding of the data analysis process, students will routinely apply what they have learned to real data using SPSS. Students will become familiar with SPSS through class lectures, in-class lab exercises, and take-home assignments. SPSS is available to BC students through BC Apps. Real-world data sets will be provided to students for use in coursework.
Estimated from the original workload response buckets. Individual sections may differ.
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