Lab 7: Control Structures

Introduction

The main purpose of this lab is to practice control structures in R:

• if and else: testing a condition and acting on it
• for: execute a loop a fixed number of times
• while: execute a loop while a condition is true
• repeat: execute an infinite loop (must break out of it to stop) • break: break the execution of a loop
• next: skip an iteration of a loop

You will need to modify the code chunks so that the code works within each of chunk (usually this means modifying anything in ALL CAPS). You will also need to modify the code outside the code chunk. When you get the desired result for each step, change Eval=F to Eval=T and knit the document to HTML to make sure it works. After you complete the lab, you should submit your HTML file of what you have completed to Canvas before the deadline.

Part 1: Vector and Control Structures

1.1 (2 points)

Write code that creates a vector x that contains 100 random observations from the standard normal distribution (this is the normal distribution with the mean equal to 0 and the variance equal to 1). Print out only the first five random observations in this vector.

#

1.2 (2 points)

Write code that replaces the observations in the vector x that are greater than or equal to 0 with a string of characters "non-negative" and the observations that are smaller than 0 with a string of characters "negative". Hint: try ifelse() funtion. Print out the first five values in this new version of x.

#

1.3 (2 points)

Write for-Loop to count how many observations in the vector x are non-negative and how many observations are negative. (There are many easier ways to solve this problem. Use for-Loop or get 0 points. Use the cat() function to print out a sentence that states how many non-negative and negative obervations there are. For example, “The number of non-negative observations is 32”.

#

Part 2: Matrix and Control Structures

2.1 (4 points)

Create a \(100000\) by \(10\) matrix A with the numbers \(1:1000000\). The first row of this matrix should be the numbers 1 to 10. The second row of this matrix should be the numbers 11 to 20. Create a for-loop that calculates the sum for each row of the matrix and save the results to a vector sum_row and print out the first five values of sum_row.

A = matrix(1:1000000, COMPLETE) # DO NOT CHANGE

Verify that your results are consistent with what you obtain with the built-in rowSums function.

sum_row_rowSums = as.integer(rowSums(A))
sum_row_rowSums[1:5]

2.2 (4 points)

Another common loop structure that is used is the while loop, which functions much like a for loop, but will only run as long as a test condition is TRUE. Modify your for loop from the previous exercise and make it into a while loop. Use the identical() function to check if the results from the for loop are the same as the results from while loop.

#

Part 3: Data Frame and Control Structures

3.1 (4 points)

Write a for loop to compute the mean of every column in mtcars and save the results to a vector col_mean. Ignore missing values when taking the mean.

#

3.2 (2 points)

Compute the number of unique values in each column of iris and print the results during a loop. Use the cat() function to print out the values in a sentence with the corresponding name of the variable. For example, “The number of unique values for Sepal.Length is 35”.

names(iris) #DO NOT CHANGE

## [1] "Sepal.Length" "Sepal.Width"  "Petal.Length" "Petal.Width"  "Species"