This course will introduce students to basic and mid-level statistical methodology. The course will familiarize the students with basic statistical concepts (median, mean, variance, etc.) and carry on to more complex statistical tools such as distributions, hypothesis testing, and more. The bulk of the course is intended for covering the most popular statistical tests in use: t-tests, chi-square, ANOVA, regressions, and more. We will discuss both parametric and non-parametric statistical tests. The principal aim of the course is to instill the students with a basic understanding of statistical thought, so they can apply statistical reasoning in new and unfamiliar areas of research.
Topics to be discussed (not necessarily in the below mentioned order):
1. Basic concepts: Measurement scales; Variables; Transformations; Data plotting
2. Central tendencies; Measures of variability
3. The Normal distribution; Sampling distributions
4. Hypothesis Testing; Type I and type II errors
5. One-sample t-test: Power; Confidence Interval
6. Two-sample t-tests (matched and independent samples)
7. Probability, Combinatorics, Bayes' rule
8. The binomial distribution; chi-square test
9. Correlation & Regression
10. Multiple Regression
11. ANOVA
12. Post-hoc comparisons
13. Repeated measures designs
14. Nonparametric tests