Homework Module 1.2 Key

Your Name (replace me)

Date (replace me)

In the questions below, use R code to answer questions. For any non-coding questions, give your answer as a comment.

1. In the code chunk below, define what a variable is (using comments), and create a variable myVariable set equal to 20.

# A variable is a letter, word, or series of words that can store a value (number, word, vector, data set) in R


myVariable<-20

2. Describe what a vector is in R, and create a sample vector below:

# A vector is a type of variable that stores multiple values

myVector<-c(1,2,3,4,5)

3. In the code chunk below, load the tidyverse. Why might we do this, and what is the tidyverse for?

library(tidyverse)

── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
✔ dplyr     1.1.4     ✔ readr     2.1.5
✔ forcats   1.0.0     ✔ stringr   1.5.1
✔ ggplot2   3.5.1     ✔ tibble    3.2.1
✔ lubridate 1.9.3     ✔ tidyr     1.3.1
✔ purrr     1.0.2     
── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()
ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

# Loading the tidyverse provides additional functions for R programming.

# The tidyverse is a series of packages and functions written by data scientists to make working with data easier.

4. Describe what a function is. What is an argument? How might you learn about what functions exist in R?

# A function is a built in command that performs common tasks.

# An argument is a thing (variable, data set, etc.) that you provide to a function as input.

# You can learn about what functions exist by searching the internet.

5. What is camel case? Describe some best practices for naming variables.

# Camel case is a syntax for creating variable names in which the first word is lower case, and subsequent words are title case, with no spaces.

# Variables should be named in such a manner that they are readable (e.g. with camel case), and that they accurately describe what the variable contains.

6. What is the mean for the survey responses for self reported willingness to settle in a remote environment (hint: use the remote column)

teamAntarcticaData<-read_csv("teamAntarcticaData.csv")

Rows: 75 Columns: 12
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (7): Timestamp, school, swim, animals, parkaColor, teamFlag, distance
dbl (5): fishing, cold, remote, bedsideManner, cooking

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

remote<-teamAntarcticaData$remote

mean(remote)

[1] 3.28

7. What does the glimpse function do (we have not covered it)? How might you learn more about it?

# glimpse() lets you view your dataset in a transposed view (columns become rows)

# You can learn more about glimpse() by running help(glimpse). You can also find documentation/look for examples by searching the internet.