Understanding the Data We Are Working With

BEFORE YOU BEGIN: 

For most examples in this book, we will be using one dataset for simplicity. The dataset contains data that we generated for educational purposes. However, most of these fictional data were created based on real published results from various articles that aimed to understand exam performance in college students, a relevant topic for most who may use this book! 

You can download the dataset here:   https://drive.google.com/file/d/1qNimbaLGqrGSgmwBc6SldYak-oUTnVDk/view?usp=sharing

And here is the key for more information about the dataset: https://drive.google.com/file/d/1WKyF1TDKF2v63QNVcb6pnzB6EQnGspKw/view?usp=sharing

The videos use the following .Rmd file:  https://drive.google.com/file/d/1CQ0q_GslIe5qV4l3VLyh5ySc69ovIDRc/view

09-B: Identifying variable types: Continuous vs. Discrete

A critical component of of data analysis is understanding the data that you have so you can compute the most appropriate statistical analyses and visualizations. Before computing any statistics on your data we want to identify if our variables are discrete or continuous.

Below is a graphical definition of continuous and discrete variables by Alison Horst and if you would like more information about this distinction you can read this overview or view this video explanation.

Video (6:16)

Test Your Knowledge

Interested in learning more? 

References