Function definition in R Programming - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of a simple function call

What is the output of the following R code?

R Programming

multiply_by_two <- function(x) {
  return(x * 2)
}

result <- multiply_by_two(5)
print(result)

A [1] 10

B [1] 7

C Error in multiply_by_two(5) : could not find function "multiply_by_two"

D [1] 25

💡 Hint

Think about what the function does to the input number.

The function multiply_by_two takes an input x and returns x multiplied by 2. So multiply_by_two(5) returns 10.

❓ Predict Output

intermediate

Function with default argument

What will be printed when this R code runs?

R Programming

greet <- function(name = "Guest") {
  print(paste("Hello," , name))
}

greet()
greet("Alice")

A

[1] "Hello, Guest"
[1] "Hello, Alice"

B

[1] "Hello, "
[1] "Hello, Alice"

C Error: object 'name' not found

D

[1] "Hello, Alice"
[1] "Hello, Guest"

💡 Hint

Check what happens when no argument is given.

The function greet uses a default value 'Guest' for the parameter name. Calling greet() prints 'Hello, Guest'. Calling greet("Alice") prints 'Hello, Alice'.

❓ Predict Output

advanced

Function with variable scope

What is the output of this R code?

R Programming

x <- 10

add_to_x <- function(y) {
  x <- 5
  return(x + y)
}

result <- add_to_x(3)
print(result)
print(x)

A

[1] 13
[1] 10

B

[1] 8
[1] 10

C

[1] 8
[1] 5

D

[1] 13
[1] 5

💡 Hint

Remember that variables inside functions have local scope.

Inside the function, x is set to 5 locally. So add_to_x(3) returns 5 + 3 = 8. The global x remains 10, so print(x) outputs 10.

❓ Predict Output

advanced

Function with missing return statement

What will this R code print?

R Programming

sum_values <- function(a, b) {
  a + b
}

result <- sum_values(4, 6)
print(result)

A Error: object 'result' not found

B NULL

C [1] 10

D [1] 46

💡 Hint

In R, the last expression is returned even without return().

In R, if there is no explicit return(), the last evaluated expression is returned. So sum_values(4, 6) returns 10.

🧠 Conceptual

expert

Error type from incorrect function call

What error will this R code produce when run?

R Programming

my_function <- function(x, y) {
  return(x + y)
}

my_function(5)

A No error, returns 5

B Error in my_function(5) : object 'y' not found

C Warning: unused argument (5)

D Error in my_function(5) : argument "y" is missing, with no default

💡 Hint

Check if all required arguments are provided.

The function requires two arguments x and y. Calling it with only one argument causes an error about missing argument y.

Practice

1. What is the correct way to start defining a function named greet in R?

easy

A. greet <- function() { }

B. function greet() { }

C. def greet() { }

D. function <- greet() { }

Solution

1. Step 1: Recognize R function syntax

   In R, functions are defined by assigning a function() to a name using <-.

2. Step 2: Match the correct syntax

   greet <- function() { } uses the correct syntax: name <- function() { }.

3. Final Answer:

   greet <- function() { } -> Option A

4. Quick Check:

   Function definition = name <- function() [OK]

Hint: Use name <- function() to define functions in R [OK]

Common Mistakes:

• Using def instead of function
• Writing function name() without <-
• Placing function keyword after name

2. Which of the following is the correct syntax to define a function add that takes two arguments x and y in R?

easy

A. function add(x, y) { x + y }

B. add(x, y) <- function { return x + y }

C. add <- function(x, y) { return(x + y) }

D. add <- function x, y { return(x + y) }

Solution

1. Step 1: Check function definition format

   In R, arguments go inside parentheses after function keyword, and the body is inside braces.

2. Step 2: Verify return statement and assignment

   add <- function(x, y) { return(x + y) } correctly assigns function with arguments and uses return() properly.

3. Final Answer:

   add <- function(x, y) { return(x + y) } -> Option C

4. Quick Check:

   Arguments inside function() and return() used [OK]

Hint: Put arguments inside function() parentheses [OK]

Common Mistakes:

• Placing arguments outside function()
• Missing braces {} around function body
• Incorrect assignment syntax

3. What will be the output of the following R code?

multiply <- function(a, b) {
  result <- a * b
  return(result)
}
multiply(3, 4)

medium

A. 12

B. 7

C. 34

D. Error

Solution

1. Step 1: Understand function behavior

   The function multiply takes two numbers and returns their product.

2. Step 2: Calculate the product of 3 and 4

   3 * 4 equals 12, so the function returns 12.

3. Final Answer:

   12 -> Option A

4. Quick Check:

   3 * 4 = 12 [OK]

Hint: Multiply inputs and return result to get output [OK]

Common Mistakes:

• Adding instead of multiplying
• Concatenating numbers as strings
• Forgetting to return the result

4. Identify the error in this R function definition:

sum_values <- function(x, y) 
  total <- x + y
  return(total)
}

medium

A. Function name is invalid

B. Missing opening brace { after function()

C. Incorrect use of return()

D. Arguments should be inside square brackets []

Solution

1. Step 1: Check function body braces

   The function body must be enclosed in braces { } immediately after function() declaration.

2. Step 2: Locate missing brace

   The code lacks an opening brace { after function(x, y), causing syntax error.

3. Final Answer:

   Missing opening brace { after function() -> Option B

4. Quick Check:

   Function body needs { } [OK]

Hint: Always put { after function() to start body [OK]

Common Mistakes:

• Omitting braces around function body
• Placing return outside function
• Using wrong brackets for arguments

5. You want to write a function filter_positive that takes a numeric vector and returns only the positive numbers. Which function definition correctly does this in R?

hard

A. filter_positive <- function(vec) { return(vec[vec == 0]) }

B. filter_positive <- function(vec) { return(vec[vec < 0]) }

C. filter_positive <- function(vec) { vec > 0 }

D. filter_positive <- function(vec) { return(vec[vec > 0]) }

Solution

1. Step 1: Understand filtering in R

   To get positive numbers, select elements where vec > 0.

2. Step 2: Check return statement

   filter_positive <- function(vec) { return(vec[vec > 0]) } returns vec elements where condition vec > 0 is TRUE, correctly filtering positives.

3. Final Answer:

   filter_positive <- function(vec) { return(vec[vec > 0]) } -> Option D

4. Quick Check:

   Filter with vec[vec > 0] returns positives [OK]

Hint: Use vec[vec > 0] to filter positive numbers [OK]

Common Mistakes:

• Using wrong comparison operator
• Not returning filtered vector
• Returning logical vector instead of values