Homework 1

Author

Your Name

Published

Invalid Date

Before your start the assignment

  • Update the header - put your name in the author argument and put today’s date in the date argument.
  • Click the “Render” button in RStudio and then open the rendered 1-hw1.html page.
  • Then go back and try changing the theme argument in the header to something else - you can see other available themes here. Notice the difference when you render now!

Overview of HW1

In this assignment, you will explore the midwest dataset using ggplot2 to uncover patterns in population, education, and poverty across counties in the U.S. Midwest.

Skills practiced:

  • Exploratory data visualization
  • Mapping variables to aesthetics (aes)
  • Practice different components of ggplot2 including geom_*(), scale_*(), facet_wrap()
  • Draw public health insights from data

Load Required Packages

library(ggplot2)
library(dplyr)

Load the Data

data(midwest)
# tip: type ?midwest in your console to see the data dictionary

Q1: Explore the dataset

Using glimpse() or summary() to explore the structure of the dataset. What are the variables in the dataset? What interesting public health questions can you ask based on the variables in the dataset? Write down at least 3 questions you can ask based on the variables in the dataset:

NoteYour Answer
  • Research question 1:
  • Research question 2:
  • Research question 3:
#your code here

Q2: Population vs. poverty

Create a scatterplot with:

  • poptotal on the x-axis
  • percbelowpoverty on the y-axis
  • Color the points by state
#your code here

What do you notice about the relationship between county population size and poverty? Do some states stand out?

NoteYour Answer

Type your response here.

Q3: Education vs. poverty

  • Make a scatterplot of percollege (x) vs percbelowpoverty (y).
  • Add a smoother using geom_smooth().
# your code here

What does this tell you about the relationship between education and poverty?

NoteYour Answer

Type your response here.

Q4: Facet by metro/non-metro

  • Recreate the scatterplot of percollege (x) vs percbelowpoverty (y).
  • Subset the data by metro and non-metro counties using facet_wrap().
# your code here

How does the relationship between education and poverty differ between metro and non-metro counties?

NoteYour Answer

Type your response here.

Q5: Compare poverty rates by state

# your code here

What differences do you observe in the poverty rate distributions across states? Which states appear to have more consistent or more variable poverty rates?

NoteYour Answer

Type your response here.

Q6: Make a visualization to answer one of the research questions you wrote down for Q1.

NoteYour Research Question

Type your research question here.

# your code here
NoteYour Answer

Type your answer to your research question based on the visualization here.

BONUS: Improve your visualization and record the evolution of your work

  • Read the blogpost by Cedric Scherer here
  • Take your visualization from Q6 and improve it. You can change the geometric object, color scheme, add labels, or any other changes you think will make it better.
  • Record the evolution of your work using the {camcorder} package and save a gif called my-ggplot-evol.gif.
#your code here

Insert the gif here:

NoteYour Answer