When should you choose an R List over an R Array?

a) When you need to store data of different types and shapes that cannot be easily organized into a multi-dimensional structure

b) When you need to perform multi-dimensional numerical computations

c) When you need to plot multi-dimensional data

d) When you need to store large numeric datasets

Answer:

a) When you need to store data of different types and shapes that cannot be easily organized into a multi-dimensional structure

Explanation:

You should choose an R list over an R array when you need to store data of different types and shapes that cannot be easily organized into a multi-dimensional structure. Lists are highly flexible and can contain elements of varying lengths and types, including other lists, matrices, or data frames.

# Creating a list with different data types and shapes
my_list <- list(
    vector_element = c(1, 2, 3),
    matrix_element = matrix(1:4, nrow = 2),
    data_frame_element = data.frame(Name = c("Alice", "Bob"), Age = c(25, 30))
)

# Printing the list
print(my_list)

# Output:
# $vector_element
# [1] 1 2 3
#
# $matrix_element
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    4
#
# $data_frame_element
#    Name Age
# 1 Alice  25
# 2   Bob  30

In this example, my_list contains a numeric vector, a matrix, and a data frame, each of different shapes and data types. Lists are particularly useful when dealing with complex datasets that do not fit neatly into a uniform structure, such as when combining various types of analyses or data sources in a single object.