Intro R Lab Solutions

In my solutions I will try to highlight the complete answer to a question using yellow. I may also include extra information to explain an answer or provide hints for similar questions we encounter in the future which I will highlight in orange.

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Question 1: Create a new R Markdown file and copy the entirety of this question over to the new file (we will do this for all questions in this lab). Then, proceed with the instructions below.

Between the stars below, do the following:

Use two # to create a header that says About Me Type your first name in bold and your last name in italics Create a bullet point list of the people sitting on either side of you Create a numbered list of your 3 least favorite animals

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Question 2: Again, copy the entirety of this question into the R Markdown file you created for Question 1.

Let’s practice creating vectors and subsetting with a short exercise.

First, create an R code chunk between the rows of stars below (Ctrl+Alt+I is quick way to do this) Next, create a vector called x that has all of the numbers from 11 to 20 Use square brackets and subsetting to select the first five numbers of this vecto

# create vector x that has numbers 11 through 20
x = 11:20

# select first 5 numbers of this list
x[1:5]

## [1] 11 12 13 14 15

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Question 3: For this question, we will be using the HappyPlanet data that we have just looked at:

• Part A Copy the code above to read the Happy Planet data into your own R Markdown file, saving the dataset to a variable called planet

# Use read.csv to pull Happy Planet data
planet <- read.csv("https://collinn.github.io/data/HappyPlanet.csv")

• Part B Looking at the Happy Planet data, explain in one or two sentences what constitutes an observation in this dataset (what is the data being recorded from)

An observation is a country. We don’t know much more about each country in terms of when, how, or why the data was recorded.

• Part C Using $ to extract columns from the dataset, find the mean life expectancy of all countries in the dataset? (Hint: what functions have we seen already in this lab?)

mean(planet$LifeExpectancy)

## [1] 67.83846

• Part D Are there any variables in this dataset that are stored as a numeric that would be better suited as a categorical variable? Explain your answer

class(planet$Region)

## [1] "integer"

The region variable is quantitative according to R. The region a country belongs to should probably be categorical with a short name describing that region. Instead, the regions listed as 1 through 7 as they are do not tell us much for context.