# Week 6: Inferential statistics I - Hypothesis testing

# Key concepts

- Standard errors
- Sampling distribution
- Law of large numbers
- Bootstrapping and Central Limit Theorem
- Confidence Intervals and p-values
- Student’s t-distributions
- Null and alternative hypotheses
- One and two-tailed tests
- Type I and type II error
- Sample size

# Before class

## Required readings

- Meier, K. J., Brudney, J. L., & Bohte, J. (2014). Introduction to Inference. In
*Applied Statistics for Public and Nonprofit Administration*. - Meier, K. J., Brudney, J. L., & Bohte, J. (2014). Hypothesis Testing. In
*Applied Statistics for Public and Nonprofit Administration*.

## Recommended readings

- Chapters 9 and 10 in: Klein, G., & Dabney, A. (2013).
*The Cartoon Introduction to Statistics*(First edition). Hill and Wang, a Division of Farrar, Straus and Giroux.

### Bunnies, Dragons and the ‘Normal’ World: Central Limit Theorem

### P-hacking and replication

# In class

- Lecture on key concepts (45 min)
- Group activity: Applying statistics (30 min)
- In class practice (1h):
- Paper practice
- In-class practice

- Assignment catch-up (if time allows):
- Qualitative Group Project (15 min).
- Quantitative Test (15 min).