Useful vector functions (length, sum, mean) in R Programming - Cheat Sheet & Quick Revision

Recall & Review

beginner

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

The length() function returns the number of elements in the vector. It tells you how many items are inside.

beginner

How does the sum() function work on a numeric vector in R?

The sum() function adds up all the numbers in the vector and gives you the total.

beginner

What is the purpose of the mean() function in R?

The mean() function calculates the average value of the numbers in a numeric vector by adding them up and dividing by the count.

beginner

If you have a vector c(2, 4, 6, 8), what will length(), sum(), and mean() return?

length() returns 4 because there are 4 numbers.
sum() returns 20 because 2+4+6+8=20.
mean() returns 5 because 20 divided by 4 is 5.

intermediate

Can sum() and mean() be used on non-numeric vectors?

No, sum() and mean() only work on numeric vectors. Using them on non-numeric vectors will cause an error.

What does length(c(1, 3, 5, 7)) return?

A 4

B 16

C 1

D Error

length() counts how many elements are in the vector, which is 4.

What is the result of sum(c(10, 20, 30))?

A 20

B Error

C 10

D 60

sum() adds all numbers: 10 + 20 + 30 = 60.

Which function calculates the average of numbers in a vector?

A length()

B mean()

C sum()

D max()

mean() calculates the average value.

What happens if you use sum() on a character vector like c('a', 'b')?

A Returns the number of characters

B Returns the concatenated string

C Gives an error

D Returns 0

sum() only works on numbers, so it gives an error on characters.

If a vector has 5 elements, what will length() return?

A 5

B 0

C Sum of elements

D Mean of elements

length() returns the count of elements, which is 5.

Explain what the functions length(), sum(), and mean() do when used on a numeric vector in R.

Think about counting, adding, and averaging.

Describe a real-life example where you might use length(), sum(), and mean() on a list of numbers.

Imagine you have a list of test scores.

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