What is a key use case for R Matrices in data analysis?
a) Performing linear algebra operations, such as matrix multiplication
b) Storing heterogeneous data types
c) Handling categorical data
d) Creating complex plots
Answer:
a) Performing linear algebra operations, such as matrix multiplication
Explanation:
R matrices are widely used in data analysis for performing linear algebra operations, such as matrix multiplication, addition, and inversion. Matrices are ideal for these tasks because they store numeric data in a structured, two-dimensional format, making them suitable for various mathematical and statistical computations.
# Creating two matrices
matrix1 <- matrix(1:4, nrow = 2, ncol = 2)
matrix2 <- matrix(5:8, nrow = 2, ncol = 2)
# Performing matrix multiplication
result_matrix <- matrix1 %*% matrix2
print(result_matrix)
# Output:
# [,1] [,2]
# [1,] 19 22
# [2,] 43 50In this example, two 2×2 matrices are created and multiplied using the %*% operator. The resulting matrix stores the product of the multiplication, showcasing how matrices are used for complex mathematical operations in R. This capability is essential for tasks like solving systems of equations, eigenvalue decomposition, and more.