---
title: "S4R: Classes 11 and 12, Plotting bivariate"
author: "Your Name Here"
date: "`r format(Sys.time(), '%B %d, %Y')`"
output:
html_document:
toc: true
---
---
# Rubric
1. (0 p) Dataset is specified.
2. (0 p) Variables from the personal codebook are indicated.
3. (10 p) One of the following (4 p for plot, 2 p for labelled axes and title, 4 p for interpretation):
* Scatter plot (for regression): $x$ = numerical, $y$ = numerical, include axis labels and a title.
Interpret the plot: describe the relationship.
* Box plots (for ANOVA): $x$ = categorical, $y$ = numerical, include axis labels and a title.
Interpret the plot: describe the relationship.
* Mosaic plot or bivariate bar plots (for contingency tables): $x$ = categorical, $y$ = categorical, include axis labels and a title.
Interpret the plot: describe the relationship.
* Logistic scatter plot (for logistic regression): $x$ = numerical, $y$ = categorical (binary), include axis labels and a title.
Interpret the plot: describe the relationship.
---
Class 13: Plot one of the four plots with a rough interpretation.
Class 14: Finish the four plots with informative labels on axes and title and clear interpretations.
The sections from Erik's `S4R_Project_All_Erik_NESARC.Rmd` file to focus on are
* Class 13 Graphing Bivariate
* Scatter plot (for regression): x = numerical, y = numerical
* Box plots (for ANOVA): x = categorical, y = numerical
* Mosaic plot or bivariate bar plots (for contingency tables): x = categorical, y = categorical
* Logistic scatter plot (for logistic regression): x = numerical, y = categorical (binary)