# Problem set 1

# Task 1: Identifying information.

Clayton (2018) considers measures of implicit bias for multiple participants from an “in-field implicit association tests”. The codebook contains a description of the data.

- What is the population under study?
- Identify the type of sampling.
- What are the observational and experimental units? How many observations are there for each in the sample?
- Comment on the quality of the sample and the generalizability of the findings.
- Identify the response variable, the factor and the treatment levels.

Consider next the first field experiment of Goldstein et al. (2008):

- Briefly describe the experimental setup
- What is the population of interest?
- Identify the experimental units and the sample size.

# Task 2: Getting started with programming

Starting from next week, you will need to perform statistical analyses using a *suitable* software of your choosing.

Your job is to install a software of your liking. Tell me which one you chose and report back on your success! Also go through tutorials to get started with loading data, producing basic plots and computing simple descriptive statistics.

## References

Clayton, A. (2018). Do gender quotas really reduce bias? Evidence from a policy experiment in Southern Africa.

*Journal of Experimental Political Science*,*5*(3), 182--194. https://doi.org/10.1017/XPS.2018.8
Goldstein, N. J., Cialdini, R. B., & Griskevicius, V. (2008). A room with a viewpoint: Using social norms to motivate environmental conservation in hotels.

*Journal of Consumer Research*,*35*(3), 472–482. https://doi.org/10.1086/586910