title: “HW 5” author: Hadiyah Sumter output: html_document —

Functions

1- Create a function named calculate_area_of_circle that takes one parameter, radius, representing the radius of a circle. The function should calculate and return the area using the formula:

area = 𝜋 × radius^2

Test your function with at least two different radii and print the results.

calculate_area_of_circle <- function (radius) {
  return(pi*radius ^2)

}

calculate_area_of_circle(5)

## [1] 78.53982

calculate_area_of_circle(10)

## [1] 314.1593

2- Write a function called check_temperature that takes a single numeric input temp.

If temp > 30, print “Hot”

If temp >= 15 & temp <= 30, print “Warm”

Otherwise, print “Cold”

Test the function on three different values (e.g., 10, 20, 35).

check_temperature <- function(temp) {
  if (temp > 30) {
    return("Hot")
  } else if (temp >= 15 & temp <= 30) {
    return("Warm")
  } else {
    return("Cold")
  }
}

check_temperature(10)

## [1] "Cold"

check_temperature(20)

## [1] "Warm"

check_temperature(35)

## [1] "Hot"

3- Write a function named sum_odd_numbers that uses a for loop to calculate the sum of all even numbers from 1 to n. The function should return the total sum.

Test the function with n = 9 and n = 39.

sum_odd_numbers <- function(n) {
  total_sum <- 0
  for (i in 1:n) {
    if (i %% 2 == 1) {  
      total_sum <- total_sum + i
    }
  }
  return(total_sum)
}
sum_odd_numbers(9)

## [1] 25

sum_odd_numbers(39)

## [1] 400

EDA

For this section, use the built-in mtcars dataset (instead of airquality). Perform the following:

• Check the structure of the dataset.

• Display the summary statistics.

• Check for any missing values.

Ask a simple question that can be answered with a basic function (e.g., What is the mean miles per gallon (mpg) across all cars?). Write the code and output the answer.

str(mtcars)

## 'data.frame':    32 obs. of  11 variables:
##  $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
##  $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
##  $ disp: num  160 160 108 258 360 ...
##  $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
##  $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
##  $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
##  $ qsec: num  16.5 17 18.6 19.4 17 ...
##  $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
##  $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
##  $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
##  $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

summary(mtcars)

##       mpg             cyl             disp             hp       
##  Min.   :10.40   Min.   :4.000   Min.   : 71.1   Min.   : 52.0  
##  1st Qu.:15.43   1st Qu.:4.000   1st Qu.:120.8   1st Qu.: 96.5  
##  Median :19.20   Median :6.000   Median :196.3   Median :123.0  
##  Mean   :20.09   Mean   :6.188   Mean   :230.7   Mean   :146.7  
##  3rd Qu.:22.80   3rd Qu.:8.000   3rd Qu.:326.0   3rd Qu.:180.0  
##  Max.   :33.90   Max.   :8.000   Max.   :472.0   Max.   :335.0  
##       drat             wt             qsec             vs        
##  Min.   :2.760   Min.   :1.513   Min.   :14.50   Min.   :0.0000  
##  1st Qu.:3.080   1st Qu.:2.581   1st Qu.:16.89   1st Qu.:0.0000  
##  Median :3.695   Median :3.325   Median :17.71   Median :0.0000  
##  Mean   :3.597   Mean   :3.217   Mean   :17.85   Mean   :0.4375  
##  3rd Qu.:3.920   3rd Qu.:3.610   3rd Qu.:18.90   3rd Qu.:1.0000  
##  Max.   :4.930   Max.   :5.424   Max.   :22.90   Max.   :1.0000  
##        am              gear            carb      
##  Min.   :0.0000   Min.   :3.000   Min.   :1.000  
##  1st Qu.:0.0000   1st Qu.:3.000   1st Qu.:2.000  
##  Median :0.0000   Median :4.000   Median :2.000  
##  Mean   :0.4062   Mean   :3.688   Mean   :2.812  
##  3rd Qu.:1.0000   3rd Qu.:4.000   3rd Qu.:4.000  
##  Max.   :1.0000   Max.   :5.000   Max.   :8.000

colSums(is.na(mtcars))

##  mpg  cyl disp   hp drat   wt qsec   vs   am gear carb 
##    0    0    0    0    0    0    0    0    0    0    0

What is the mean miles per gallon (mpg) across all cars?

mean(mtcars$disp)

## [1] 230.7219