https://drive.google.com/file/d/1sz32tfzRPM1DgkDpm57ZL2pwVHYrG0oN/view?usp=sharing

The link above is data

# Upload the epa data set

# call the dataset cardata

cardata = read.csv(file.choose(), header = TRUE)

View(cardata)

# A side by side boxplot

boxplot(FiveYearEstimatedCost~Guzzler, data = cardata,

main = "add title",

xlab = "add horizontal axis name",

col = c("red", "green"), ### add different color names

horizontal = TRUE)

# Calculate the mean, sd and sample sizes for five year fuel cost split among Guzzler and no Guzzler

# the command aggregate() will perform the given function on the specified groups

# aggregate(response~treatment, data = datasetname, function)

# Make a table of values with the results.

aggregate(FiveYearEstimatedCost~Guzzler, data = cardata, mean)

aggregate(FiveYearEstimatedCost~Guzzler, data = cardata, sd)

aggregate(FiveYearEstimatedCost~Guzzler, data = cardata, length)

# What type of vehicles are Guzzlers? Find out by subsetting the dataset to only include Guzzlers.

GuzzlersOnly = subset(cardata, Guzzler == "Guzzler")

View(GuzzlersOnly)

# Perform a two sample t test

# Use the same response~treatment format as the functions above.

# t.test(response~treatment, data = datasetname, conf.level = enterconfidencelevel, alternative = "two.sided" ))

For the last part of the data , that is this part. create code for it.

# Perform a two sample t test

# Use the same response~treatment format as the functions above.

# t.test(response~treatment, data = datasetname, conf.level = enterconfidencelevel, alternative = "two.sided" ))