Homework Two: Due Oct. 1 at 5 pm.

First, we will use a modified version of surveys.csv, which has some strange values entered for NAs. Download like so:

download.file(url = "https://raw.githubusercontent.com/BiologicalDataAnalysis2019/2021/master/homeworks/HomeworkTwo.Rmd", destfile = "/cloud/project/homeworks/HomeworkTwo.Rmd")
download.file("https://raw.githubusercontent.com/BiologicalDataAnalysis2019/2021/master/homeworks/HW2_data/surveys_odd_NA_values.csv", destfile = "/cloud/project/data/surveys_odd_NA_values.csv")

In your RStudio interface, you will note that there is now a “Homeworks” directory. In it, you will find “HomeworkTwo.Rmd”. In your RStudio instance, open it.

Each question will direct you to perform a task. Each question that expects code as an answer will have a space for you to enter the code.

You are welcome, and even encouraged, to work with a partner. I do ask, though, that every member submits their own homework. To submit your homework, simply save it. I will see it.

Question One - 1 point.

Load in the surveys.csv data file that is located in your homework folder, and save it to a variable called surveys. Use the read_csv function in the tidyverse package to do this.

#Enter your answer for Question 1 here

Question Two - 1 point

Have a look at the copy of surveys.csv. You will notice that there are some unusual NA values. Particularly, the “species_id” column has some odd values. Look at the help page for read_csv. Can you find a way to read these unusual values as NAs? Are you able to process both NA and the odd value as NAs? Try it out.

#Enter your answer for Question 2 here

Question Three - 1 point

Remove the NA values from the hindfoot_length column using a pipe and a filter.

#Enter your answer for Question 3 here

Question Four - 2 points

Verify that the NA values were removed. Don’t do this by looking at the column - use code.

#Enter your answer for Question 4 here

Question Five - 1 point

Explain the logic of your answer to Question Four. How did you accomplish this?

Question Six - 1 point

Imagine you are testing the hypothesis that mammal body sizes will be larger under climate change to decrease surface to body size ratio. First, what columns in the dataframe will you use to address this question?

Question Seven - 2 points

Let’s try some analysis: Use a filter, a group_by, and a summarize to decide if you think mammal body sizes are decreasing under climate change.

Question Eight - 1 points

Based on the outputs of question 7, does it look like mammal body sizes are decreasing over time?