Why vectors are the fundamental data structure in R Programming - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a numeric vector with elements 1, 2, and 3.

R Programming

vec <- c([1])

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

A"1", "2", "3"

B1, 2, 3

Cc(1, 2, 3)

Dlist(1, 2, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Putting numbers inside quotes creates a character vector, not numeric.

Using list() creates a list, not a vector.

The c() function combines values into a vector. Using 1, 2, 3 creates a numeric vector.

2fill in blank

medium

Complete the code to get the length of the vector vec.

R Programming

len <- [1](vec)

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Alength

Bcount

Csize

Ddim

Attempts:

3 left

💡 Hint

Common Mistakes

Using dim() returns NULL for vectors.

Using size() or count() are not valid R functions.

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

3fill in blank

hard

Fix the error in the code to access the second element of vector vec.

R Programming

second_element <- vec[1]2

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A[[

B(

C{

D[

Attempts:

3 left

💡 Hint

Common Mistakes

Using double brackets [[ ]] causes errors with vectors.

Using curly braces or parentheses for indexing is invalid.

Use single square brackets [] to access elements of a vector by position.

4fill in blank

hard

Fill both blanks to create a vector of even numbers from 2 to 10.

R Programming

evens <- seq([1], [2], by = 2)

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A2

B1

C10

D12

Attempts:

3 left

💡 Hint

Common Mistakes

Starting at 1 creates odd numbers.

Ending at 12 includes a number beyond 10.

The seq() function creates sequences. Starting at 2 and ending at 10 with step 2 gives even numbers.

5fill in blank

hard

Fill both blanks to create a named vector with scores for Alice and Bob, then access Bob's score.

R Programming

scores <- c(Alice = [1], Bob = [2])
bob_score <- scores"Bob"

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

A85

B90

C[

D$

Attempts:

3 left

💡 Hint

Common Mistakes

Using $ to access vector elements causes errors.

Mixing up Alice's and Bob's scores.

Named vectors assign values with names. Use square brackets with the name to access an element.

Practice

1. Why are vectors considered the fundamental data structure in R?

easy

A. Because they are only used for storing single values

B. Because they can hold different types of data in one vector

C. Because they hold many values of the same type in order

D. Because they are slower to process than lists

Solution

1. Step 1: Understand vector properties in R

   Vectors store multiple values but all must be of the same type, arranged in order.

2. Step 2: Compare with other data structures

   Unlike lists, vectors cannot hold mixed types, and they are the basic building block for data in R.

3. Final Answer:

   Because they hold many values of the same type in order -> Option C

4. Quick Check:

   Vectors = same type, ordered values [OK]

Hint: Remember vectors hold same-type ordered values [OK]

Common Mistakes:

• Thinking vectors can hold mixed data types
• Confusing vectors with lists
• Assuming vectors store single values only

2. Which of the following is the correct way to create a vector of numbers 1, 2, and 3 in R?

easy

A. vector(1, 2, 3)

B. array(1, 2, 3)

C. list(1, 2, 3)

D. c(1, 2, 3)

Solution

1. Step 1: Recall vector creation syntax in R

   The function c() combines values into a vector.

2. Step 2: Check other options

   vector() creates an empty vector with specified length and mode, list() creates a list, and array() creates multi-dimensional arrays.

3. Final Answer:

   c(1, 2, 3) -> Option D

4. Quick Check:

   Use c() to create vectors [OK]

Hint: Use c() to combine values into a vector [OK]

Common Mistakes:

• Using vector() with values directly
• Confusing list() with vector creation
• Using array() for simple vectors

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

v <- c(10, 20, 30)
typeof(v)

medium

A. "double"

B. "integer"

C. "list"

D. "character"

Solution

1. Step 1: Understand default numeric type in R vectors

   By default, numbers with decimals or without are stored as double precision floating point numbers.

2. Step 2: Check the vector values

   The vector contains 10, 20, 30 which are numeric literals without explicit integer suffix, so they are doubles.

3. Final Answer:

   "double" -> Option A

4. Quick Check:

   Numeric vectors default to double type [OK]

Hint: Numeric vectors default to double unless specified [OK]

Common Mistakes:

• Assuming numeric literals are integers by default
• Confusing list type with vector type
• Expecting character type from numbers

4. Identify the error in the following R code that tries to create a vector:

v <- c(1, "two", 3)

medium

A. The vector contains mixed types, so R converts all to character

B. The code will cause a syntax error

C. The vector will only contain numeric values

D. The vector will be empty

Solution

1. Step 1: Analyze vector type coercion rules

   R forces all elements in a vector to be the same type, so it converts numbers to characters if any element is character.

2. Step 2: Check the given vector elements

   Since "two" is a character, 1 and 3 are converted to characters, so the vector becomes character type.

3. Final Answer:

   The vector contains mixed types, so R converts all to character -> Option A

4. Quick Check:

   Mixed types in vector cause coercion to character [OK]

Hint: Mixed types in vector become character type [OK]

Common Mistakes:

• Expecting syntax error from mixed types
• Assuming numeric values stay numeric
• Thinking vector will be empty

5. You want to create a vector that holds the ages of a group of people: 25, 30, 22, and 28. Then you want to add 5 years to each age. Which R code correctly does this using vectors?

hard

A. ages <- c(25, 30, 22, 28)
ages <- ages - 5

B. ages <- c(25, 30, 22, 28)
ages <- ages + 5

C. ages <- c(25, 30, 22, 28)
ages <- ages * 5

D. ages <- list(25, 30, 22, 28)
ages <- ages + 5

Solution

1. Step 1: Create a numeric vector of ages

   Use c() to create a vector holding the ages.

2. Step 2: Add 5 to each element

   Adding a number to a vector adds it to each element element-wise.

3. Final Answer:

   ages <- c(25, 30, 22, 28) ages <- ages + 5 -> Option B

4. Quick Check:

   Vector arithmetic applies element-wise [OK]

Hint: Use c() and + for element-wise addition [OK]

Common Mistakes:

• Using list() instead of c() for vector
• Multiplying instead of adding
• Subtracting instead of adding