Question

PLEASE NUMBER EACH ANSWER

Students will use advanced looping methods including replicate(), lapply(), sapply(), and apply(), and access datasets provided with R packages in an R script.

1. The function call, rnorm(1), generates a normal random number. Use replicate() to generate 10 normal random numbers and assign them to a vector called nums.
   
2. The R statement, data(iris), loads the built-in R data set iris. This dataset has 150 rows and 5 columns. The 5 column names are "Sepal.Length","Sepal.Width","Petal.Length","Petal.Width" and "Species".
   1. Write R code(s) to return a list of 4 items that correspond to the averages of the first 4 columns in iris. The contents of the list should be as follows:
      
      $Sepal.Length
      [1] 5.843333
      
      $Sepal.Width
      [1] 3.057333
      
      $Petal.Length
      [1] 3.758
      
      $Petal.Width
      [1] 1.199333
      
3. With the iris dataset still loaded,
   1. write R code(s) to return a vector of 4 items that correspond to the averages of the first 4 columns in iris. The contents of the vector should be as follows:

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width
5.843333	3.057333	3.7580000	1.199333

4. The following R code converts the contents of the first 4 columns in iris to a matrix called data.
   data=as.matrix(iris[,1:4])
   1. Write R code(s) to use apply() to return a vector that contains the max values of the 4 columns. The contents of the vector should be as follows [Hint, use max()]:

Sepal.Length	Sepal.Width	Petal.Length	Petal.Width
7.9	4.4	6.9	2.5

5. Write R code(s) to read the contents of the provided file COS-206-ShoppingCart.html into a variable called cart and then show the first 5 lines of cart.

Answer 1