Data Analysis Guide 2.0 in R

This book takes a project-based approach for Data Analysis using the following steps:

1. Univariate analysis – exploring the descriptive statistics of variables using methods of summarization and visualization.

2. Bivariate analysis – to find associations between two variables and measure the significance of such associations.

2.1 Simple Linear regression along with regression diagnostics

3. Multivariate Analysis – to find an association between one response and more than one explanatory variable

3.1 Multiple Linear regression along with regression diagnostics

3.2 Comparing models using adjusted R2, AIC, and ANOVA

3.3 Stepwise regression

3.4 Parallel slopes model

3.5 Using Interaction terms for modeling