STSCI 2120: Discussion 1

Introduction

Verify that R and RStudio are downloaded following Lecture 1.
Open RStudio.
In the console enter separately each of the following command lines:

1+1

[1] 2

die <- 1:6

die + die

[1]  2  4  6  8 10 12

Exercise 1

1. Choose any number and add 2 to it.
   
2. Multiply the result by 3.
   
3. Subtract 6 from the answer.
   
4. Divide what you get by 3.
   

# We choose the number 101
a <- 101 + 2
b <- a * 3
c <- b - 6
d <- c / 3
print(d)

[1] 101

Exercise 2

Define the function “magic” that takes a number as an argument and repeat the steps from Exercise 1. Set “10” as the default value.

magic <- function(x){
  y <- x + 2
  z <- y*3
  w <- z - 6
  v <- w/3
  v
}

Call the function “magic” with different values passed as arguments.

magic(10)
magic(2)
magic(7)
magic(1053)

Exercise 3

Write a function named “simple_math” that takes two numbers as input and returns both their sum and their product. Include default values for both arguments.

simple_math <- function(x = 101, y = 1024) {
    sum_result <- x+y
    product_result <- x*y
    return(list(sum = sum_result, product = product_result))
}

Test your function

result <- simple_math()
print(result)

result <- simple_math(3, 4)
print(result)

Exercise 4

Let x3 be the following vector

x3 <- c(0, 1, 1, 2, 2, 2, 3, 3, 4)

Imagine what a histogram of x3 would look like. Assume that the histogram has a bin width of 1. How many bars will the histogram have? Where will they appear? How high will each be?

When you are done, plot a histogram of x3 with binwidth = 1, and see if you are right.

# You can make a histogram of x3 with qplot(x3, binwidth = 1). The histogram will look like a symmetric pyramid. The middle bar will have a height of 3 but be sure to try it and see for yourself.
# You can use a histogram to display visually how common different values of x are. Numbers covered by a tall bar are more common than numbers covered by a short bar.

Exercise 5

Step 1

The ggplot2 package is a powerful tool for creating a wide range of plots and visualizations in R. 1. Install the ggplot2 package using the following command:

install.packages("ggplot2")

Confirm that the package has been installed by checking the output in your console.

Step 2

After installing the package, load it into your R session:

library(ggplot2)

Step 3

Let’s create a scatter plot to visualize the relationship between two sets of numbers.

1. Create two vectors of numbers:

x_values <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
y_values <- c(2, 3, 5, 7, 11, 13, 17, 19, 23, 29)

2. Use ggplot2 to create a scatter plot directly from these vectors:

ggplot() +
  geom_point(aes(x = x_values, y = y_values)) +
  labs(title = "Scatter Plot of x vs. y",
       x = "X Values",
       y = "Y Values")

Explanations

The ggplot() function initializes the plotting environment.
geom_point(aes(x = x_values, y = y_values)) creates a scatter plot with points defined by x_values and y_values.
labs() adds labels and a title to your plot.