Why matrices handle tabular math in R Programming - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a 2x2 matrix with numbers 1 to 4.

R Programming

mat <- matrix([1], nrow = 2, ncol = 2)

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

Ac(1, 2, 3)

B1:4

Cseq(1, 5)

Dc(1, 2)

Attempts:

3 left

💡 Hint

Common Mistakes

Using a vector with fewer or more elements than needed.

The matrix() function needs a vector of values. 1:4 creates numbers 1 to 4, perfect for a 2x2 matrix.

2fill in blank

medium

Complete the code to access the element in the first row and second column of the matrix.

R Programming

value <- mat[[1] , 2]

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

A0

B2

C1

D3

Attempts:

3 left

💡 Hint

Common Mistakes

Using 0 as an index, which is invalid in R.

Matrix rows and columns start at 1 in R. To get the first row, use 1.

3fill in blank

hard

Fix the error in the code to multiply two matrices correctly.

R Programming

result <- mat1 [1] mat2

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

A%*%

B*

C%

D%%

Attempts:

3 left

💡 Hint

Common Mistakes

Using * instead of %*% causes element-wise multiplication, not matrix multiplication.

Matrix multiplication in R uses the operator %*%. The * operator does element-wise multiplication.

4fill in blank

hard

Fill both blanks to create a matrix with 3 rows and 2 columns using numbers 1 to 6.

R Programming

mat <- matrix([1], nrow = [2], ncol = 2)

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

A1:6

B3

C2

Dc(1, 2, 3)

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong number of values or wrong row count.

Use 1:6 for values and 3 for number of rows to get a 3x2 matrix.

5fill in blank

hard

Fill all three blanks to create a matrix from vector 'v', with 2 rows, 3 columns, and fill by row.

R Programming

mat <- matrix([1], nrow = [2], ncol = [3], byrow = TRUE)

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

Av

B2

C3

DFALSE

Attempts:

3 left

💡 Hint

Common Mistakes

Confusing nrow and ncol values or forgetting to set byrow.

Use vector v, set rows to 2, columns to 3, and byrow = TRUE to fill matrix by rows.

Practice

1. Why are matrices useful for tabular math in R?

easy

A. Because they organize data in rows and columns for easy calculations

B. Because they store only text data

C. Because they can only hold one number

D. Because they automatically create graphs

Solution

1. Step 1: Understand matrix structure

   Matrices arrange data in rows and columns, like a table.

2. Step 2: Recognize usefulness for math

   This structure makes it easy to perform math operations on the data.

3. Final Answer:

   Because they organize data in rows and columns for easy calculations -> Option A

4. Quick Check:

   Matrix = rows + columns for math [OK]

Hint: Think tables: rows and columns help math [OK]

Common Mistakes:

• Confusing matrices with lists
• Thinking matrices hold only text
• Believing matrices create graphs automatically

2. Which of the following is the correct way to create a 2x3 matrix in R with numbers 1 to 6?

easy

A. matrix(1:6, 3, 2, byrow=TRUE)

B. matrix(1:6, nrow=3, ncol=2)

C. matrix(1:6, rows=2, cols=3)

D. matrix(1:6, nrow=2, ncol=3)

Solution

1. Step 1: Recall matrix() syntax

   The correct syntax uses nrow and ncol to specify dimensions.

2. Step 2: Match dimensions to question

   We want 2 rows and 3 columns, so nrow=2 and ncol=3.

3. Final Answer:

   matrix(1:6, nrow=2, ncol=3) -> Option D

4. Quick Check:

   nrow=2 and ncol=3 creates 2x3 matrix [OK]

Hint: Use nrow and ncol to set matrix size [OK]

Common Mistakes:

• Swapping nrow and ncol values
• Using wrong argument names like rows or cols
• Forgetting to specify dimensions

3. What is the output of this R code?

m <- matrix(1:6, nrow=2, ncol=3)
m * 2

medium

A. [2 6 10; 4 8 12]

B. [1 2 3; 4 5 6]

C. [1 4 9; 16 25 36]

D. Error: non-numeric matrix

Solution

1. Step 1: Create the matrix

   The matrix m is:
   1 3 5
   2 4 6 (since R fills by column)

2. Step 2: Multiply each element by 2

   Each number doubles:
   2 6 10
   4 8 12

3. Final Answer:

   [2 6 10; 4 8 12] -> Option A

4. Quick Check:

   Element-wise multiply by 2 = doubled values [OK]

Hint: Matrix * number doubles each element [OK]

Common Mistakes:

• Assuming matrix fills by row by default
• Confusing element-wise multiply with matrix multiplication
• Expecting error on numeric operation

4. Identify the error in this R code that tries to create a 3x2 matrix:

matrix(1:6, nrow=3, ncol=2, byrow=TRUE, fill=TRUE)

medium

A. nrow and ncol values are swapped

B. 'byrow' must be FALSE for numeric matrices

C. 'fill' is not a valid argument for matrix() function

D. matrix() cannot create 3x2 matrices

Solution

1. Step 1: Check matrix() arguments

   Valid arguments include nrow, ncol, byrow, but not 'fill'.

2. Step 2: Identify invalid argument

   The 'fill=TRUE' is not recognized and causes an error.

3. Final Answer:

   'fill' is not a valid argument for matrix() function -> Option C

4. Quick Check:

   Invalid argument causes error [OK]

Hint: Only use documented matrix() arguments [OK]

Common Mistakes:

• Assuming 'fill' is valid argument
• Thinking byrow must be FALSE
• Believing matrix size is limited

5. You have a data frame with 4 rows and 3 columns of numbers. You want to convert it to a matrix and multiply each value by 10. Which R code correctly does this?

hard

A. mat <- as.data.frame(df); mat * 10

B. mat <- as.matrix(df); mat * 10

C. mat <- matrix(df); mat * 10

D. mat <- matrix(df, nrow=4, ncol=3); mat + 10

Solution

1. Step 1: Convert data frame to matrix

   Use as.matrix() to convert df to matrix preserving data.

2. Step 2: Multiply matrix elements by 10

   Multiplying mat * 10 scales each element correctly.

3. Final Answer:

   mat <- as.matrix(df); mat * 10 -> Option B

4. Quick Check:

   as.matrix + element-wise multiply = correct [OK]

Hint: Use as.matrix() to convert before math [OK]

Common Mistakes:

• Using matrix() directly on data frame
• Trying to multiply data frame directly
• Adding 10 instead of multiplying