STA 15A Introduction to Statistical Data Science I


Learning Outcomes:
1. Gain a basic understanding of randomness/sampling variation
2. Understand why it is important to distinguish between different data types
3. Gain intuition about observed values and population counterparts
4. Learn and gain intuition about basic probability models
5. Learn how to apply and interpret outcomes of some basic statistical methodologies (hypothesis test, confidence regions)

Course Content:
1. What is randomness? Why do we need statistics?
2. Observations and random variables, is there a difference?
3. What is a statistical model?
4. Gain intuition about basic probability models.
5. Principles of statistical summaries (mean, proportion, median, variance).
6. Understanding differences between observed values and corresponding population values.
7. What is a sampling distribution and why do we need to understand this notion?
8. Hypothesis testing and confidence intervals for population mean and population proportion.

Illustrative Reading:
1. Freedman, D., Pisani, R. and Purves, R. (2007). Statistics, 4th Edition. W. W. Norton and Company.
2. Ramsey, F. and Schafer, D. (2012). The Statistical Sleuth: A Course in Methods of Data Analysis, 3rd Edition. Cengage Learning.

Potential Overlap:
The course has significant overlap with the content of STA 013. However, some materials like regression are not covered in this course. Also, the emphasis is on a more intuitive, and less formal, introduction to the core concepts of statistics than is done in STA 013. There is also some overlap in content with STA 032 and STA 100. However, those two courses require higher levels of involvement of mathematical and computational tools.

History:
None