## 9.1 Bivariate Graphing

(C $$\rightarrow$$ C) Prevalence of Nicotine Dependence (C) by Depression Status (C) (among current, daily, young adult smokers $$\rightarrow$$ values stored in nesarc created in chapter 7)

library(ggplot2)
library(PDS)
ggplot(data = nesarc, aes(x = MajorDepression, fill = TobaccoDependence)) +
geom_bar(position = "fill") +
theme_bw() +
labs(x = "", y = "Fraction",
title = "Fraction of young adult daily smokers\nwith and without nicotine addiction\nby depression status") +
scale_fill_manual(values = c("green", "red"), name = "Tobacco Addiction Status") +
guides(fill = guide_legend(reverse = TRUE)) Mosaic Plots

library(vcd)
mosaic(~TobaccoDependence + MajorDepression ,data = nesarc, shade = TRUE) ($$C \rightarrow Q$$) Boxplots and Violin plots

ggplot(data = frustration, aes(x = Major, y = Frustration.Score)) +
geom_boxplot() +
theme_bw() +
labs(x = "", y = "Frustration Score", title = "Frustration Score by\n Academic Major") # Violin plots
ggplot(data = frustration, aes(x = Major, y = Frustration.Score)) +
geom_violin() +
theme_bw() +
labs(x = "", y = "Frustration Score", title = "Frustration Score by\n Academic Major") (Q $$\rightarrow$$ Q) Scatter plots

library(PASWR2)
ggplot(data = GRADES, aes(x = sat, y = gpa)) +
geom_point(color = "lightblue") +
theme_bw() +
labs(x = "SAT score", y = "First semester college Grade Point Average") +
geom_smooth(method = "lm") ($$Q \rightarrow C$$) Scatter plot for logistic regression

library(ISLR)
library(ggplot2)
Default$defaultN <- ifelse(Default$default == "No", 0, 1)
Default$studentN <- ifelse(Default$student =="No", 0, 1)
ggplot(data = Default, aes(x = balance, y = defaultN)) +
geom_point(alpha = 0.5) +
theme_bw() +
stat_smooth(method = "glm", method.args = list(family = "binomial")) +
labs(y = "Probability of Default") 