We take a look at the basics. Installing R, loading data, installing and loading packages.

We take a look at the basics of data manipulation with dplyr and tidyr. Pipes and usual manipulation tasks in the social sciences.

SGT. [Link] [Markdown File]

Slides and Practice. [Slides] [Answers on Markdown]

Contest.

Intro to ggplot and bivariate plots.

A deeper dive into visualization. Univariate plots and non-data plot characteristics.

Univariate and multivariate outliers. Alpha and Exploratory factor analysis for survey data.

Mean comparisons galore: t tests, ANOVAS, ANCOVAS, and their non parametric counterparts.

Association. Correlation and partial correlation, regression with single and multiple predictors. Assumptions.

When the relationship between two variables is explained by or depends upon the level of a third variable.

What to do when your data is not usual. Logistic regression, Negative Binomial Regression, Poisson and others.

How to customize R to make it do exactly what you want. Write efficient code.

Say goodbye with a final conclusion