In kimgannon/bis557: Contains Homework Assignments for BIS 557 2020

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(bis557)
library(palmerpenguins)
library(DT)
data("penguins")
datatable(penguins)

Above is the penguins data set from the {palmerpenguins} package.

Selecting variables in a table

library(dplyr)
library(ggplot2)

#The "base" way
table(penguins$species, penguins$island)

#The "tidy" way
penguins %>%
  select(species, island) %>% 
  table()

Filtering rows in a table

#Base
adelies <- penguins[penguins$species == "Adelie",]
table(adelies$sex)

#Tidy
penguins %>%
  filter(species == "Adelie") %>%
  select(sex) %>%
  table()

Building a model

Let's fit the model:

$$ \text{bill_length_mm} \sim \text{species} \beta_1 + \text{island}\beta_2 + \text{sex}\beta_3 + \beta_0 $$

To fit the model, we'll run the following code:

fit <- lm(bill_length_mm ~ species + island + sex, data=penguins)
summary(fit)

Plot the residuals

#base
qs <- qqnorm(fit$residuals, plot.it = FALSE)
qsd <- as.data.frame(qs)
ggplot(qsd, aes(x=x, y=y)) + geom_point() + xlab("Theoretical Quantiles") + ylab("Sample Quantiles") + theme_minimal()

#tidy 
qs <- qqnorm( fit$residuals, plot.it = FALSE) %>%
  as_tibble() %>%
  ggplot(aes(x=x, y=y)) + geom_point() + xlab("Theoretical Quantiles") + ylab("Sample Quantiles") + theme_minimal()