Useful vector functions (length, sum, mean) in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to find the number of elements in the vector v.

R Programming

len <- [1](v)

Drag options to blanks, or click blank then click option'

Amean

Blength

Csum

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum() instead of length() to count elements.

Using mean() which calculates average, not count.

The length() function returns the number of elements in a vector.

2fill in blank

medium

Complete the code to calculate the total sum of the vector v.

R Programming

total <- [1](v)

Drag options to blanks, or click blank then click option'

Alength

Bmean

Ccount

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using length() which counts elements, not sums them.

Using mean() which calculates average.

The sum() function adds all the numbers in the vector together.

3fill in blank

hard

Fix the error in the code to calculate the average of vector v.

R Programming

avg <- [1](v)

Drag options to blanks, or click blank then click option'

Amean

Blength

Csum

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using sum() which adds numbers but does not average.

Using length() which counts elements.

The mean() function calculates the average value of the vector.

4fill in blank

hard

Fill both blanks to create a vector with word lengths greater than 3.

R Programming

lengths <- [1](words[[2](words) > 3])

Drag options to blanks, or click blank then click option'

Anchar

Blength

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using length() which counts elements in a vector, not characters in a string.

Using sum() which adds numbers, not counts characters.

The nchar() function returns the number of characters in a word. We use it to get length and to compare if length is greater than 3.

5fill in blank

hard

Fill all three blanks to create uppercase words with character count greater than 4.

R Programming

result <- [1](words[[2](words) [3] 4])

Drag options to blanks, or click blank then click option'

Atoupper

Bnchar

C>

Dtolower

Attempts:

3 left

💡 Hint

Common Mistakes

Using tolower() instead of toupper() for uppercase conversion.

Using length() instead of nchar() for character count.

toupper() converts words to uppercase, nchar() counts characters, and > checks if greater than 4.

Practice

1. What does the length() function do when applied to a vector in R?

easy

A. It calculates the sum of all elements in the vector.

B. It sorts the elements in the vector.

C. It finds the average value of the elements in the vector.

D. It returns the number of elements in the vector.

Solution

1. Step 1: Understand the purpose of length()

   The length() function counts how many items are inside a vector.

2. Step 2: Compare with other functions

   Unlike sum() or mean(), it does not add or average values, just counts them.

3. Final Answer:

   It returns the number of elements in the vector. -> Option D

4. Quick Check:

   length() = count elements [OK]

Hint: Remember length() counts items, sum() adds, mean() averages [OK]

Common Mistakes:

• Confusing length() with sum() or mean()
• Thinking length() returns the last element
• Assuming length() sorts the vector

2. Which of the following is the correct syntax to calculate the mean of a vector v in R?

easy

A. mean(v)

B. mean = v

C. mean[v]

D. mean v()

Solution

1. Step 1: Recall function call syntax in R

   Functions are called with parentheses and the vector inside, like mean(v).

2. Step 2: Check each option

   mean(v) uses correct syntax. Options B, C, and D are invalid or incorrect syntax.

3. Final Answer:

   mean(v) -> Option A

4. Quick Check:

   Function call uses parentheses: mean(v) [OK]

Hint: Use parentheses to call functions with arguments in R [OK]

Common Mistakes:

• Using square brackets instead of parentheses
• Assigning mean instead of calling it
• Omitting parentheses after function name

3. What is the output of the following R code?

v <- c(2, 4, 6, 8)
sum(v) + length(v)

medium

A. 20

B. 22

C. 24

D. 26

Solution

1. Step 1: Calculate sum(v)

   The vector v is c(2,4,6,8). Sum is 2+4+6+8 = 20.

2. Step 2: Calculate length(v) and add

   Length is number of elements = 4. Adding sum + length = 20 + 4 = 24.

3. Final Answer:

   24 -> Option C

4. Quick Check:

   sum=20 + length=4 = 24 [OK]

Hint: Add sum and length values separately, then combine [OK]

Common Mistakes:

• Adding elements incorrectly
• Confusing length with sum
• Forgetting to add length to sum

4. The following R code is intended to calculate the mean of vector x. What is wrong?

x <- c(5, 10, 15)
mean = mean(x)
print(mean)

medium

A. The print() function cannot print variables.

B. The variable name 'mean' overwrites the function mean(), causing errors later.

C. The vector x is not defined correctly.

D. mean() function requires two arguments.

Solution

1. Step 1: Analyze variable assignment

   Assigning mean = mean(x) overwrites the built-in mean() function with a number.

2. Step 2: Understand consequences

   After this, calling mean() again will cause errors because mean is no longer a function.

3. Final Answer:

   The variable name 'mean' overwrites the function mean(), causing errors later. -> Option B

4. Quick Check:

   Don't name variables same as functions [OK]

Hint: Avoid naming variables same as function names [OK]

Common Mistakes:

• Thinking print() cannot print variables
• Believing mean() needs two arguments
• Ignoring variable shadowing of functions

5. You have a numeric vector nums with some missing values (NA). Which R code correctly calculates the mean ignoring the missing values?

hard

A. mean(nums, na.rm = TRUE)

B. mean(nums, remove.na = TRUE)

C. sum(nums) / length(nums)

D. mean(nums, na.ignore = TRUE)

Solution

1. Step 1: Understand NA handling in mean()

   To ignore missing values, use the argument na.rm = TRUE inside mean().

2. Step 2: Check each option

   mean(nums, na.rm = TRUE) uses correct argument na.rm. Options B and D use incorrect argument names. sum(nums) / length(nums) does not handle NA and will return NA.

3. Final Answer:

   mean(nums, na.rm = TRUE) -> Option A

4. Quick Check:

   Use na.rm=TRUE to ignore NA in mean() [OK]

Hint: Use na.rm=TRUE to skip NA values in mean() [OK]

Common Mistakes:

• Using wrong argument names like remove.na or na.ignore
• Calculating mean manually without handling NA
• Ignoring that NA causes mean() to return NA