Imagine you need to create a recursive function in R that computes the nth Fibonacci number. How would you do this?
- fibonacci <- function(n) { if (n <= 1) { return(n) } else { return(fibonacci(n - 1) + fibonacci(n - 2)) } }
- fibonacci <- function(n) { if (n <= 1) { return(0) } else { return(fibonacci(n) + fibonacci(n - 1)) } }
- fibonacci <- function(n) { if (n <= 1) { return(1) } else { return(fibonacci(n + 1) + fibonacci(n - 1)) } }
- All of the above
To create a recursive function in R that computes the nth Fibonacci number, you can use the following code: fibonacci <- function(n) { if (n <= 1) { return(n) } else { return(fibonacci(n - 1) + fibonacci(n - 2)) } }. The function checks if the input n is less than or equal to 1. If it is, it returns n (base case). Otherwise, it recursively calls itself to calculate the Fibonacci number by summing the two previous Fibonacci numbers.
Suppose you're asked to write a function in R that takes an array of numbers and returns a new array with each element squared. How would you do it?
- Use a nested for loop to iterate over each element and calculate the square
- Use the apply() function with a custom function to calculate the square of each element
- Use the ^ operator to raise the array to the power of 2
- Use the sqrt() function to calculate the square root of each element
To write a function in R that takes an array of numbers and returns a new array with each element squared, you can use a nested for loop to iterate over each element of the array and calculate the square. By storing the squared values in a new array, you can return the resulting array as the output of the function.
What are some primary uses of the R programming language?
- Data Cleaning
- Machine Learning
- Statistical Analysis
- Web Development
While R can be used for data cleaning and machine learning, its primary focus and strength lie in statistical analysis. It provides an extensive array of libraries and tools for statistical modeling. However, it's less commonly used for web development, which is usually handled by languages like JavaScript, Python, Ruby, etc.
Can you calculate the median of a matrix in R?
- Yes, using the apply() function
- No, R does not support calculating the median of a matrix
- Yes, but it requires writing a custom function
- Yes, using the median() function directly
Yes, you can calculate the median of a matrix in R using the apply() function. By specifying the appropriate margin argument (1 for rows, 2 for columns), you can apply the median() function across the specified dimension to calculate the median values.
Can you discuss how R handles missing data in datasets?
- R represents missing data with the NA value
- R removes observations with missing data from calculations
- R assigns a default value to missing data
- R displays an error when encountering missing data
R handles missing data in datasets by representing missing values with the NA value. The NA value is a special reserved value in R that indicates missing or unavailable data. Functions in R are designed to handle NA values appropriately, such as excluding them from calculations or providing options to handle missing values in specific analyses.
The syntax as.character(number) in R is used to convert a ________ to a string.
- all of the above
- double
- integer
- numeric
In R, the as.character() function is used to convert numeric data (which includes integers, doubles, etc.) to a string. For example, as.character(123) would return "123".
In R, the boolean values are represented as ________ and ________.
- TRUE and FALSE
- 1 and 0
- T and F
- Y and N
In R, the boolean values are represented as TRUE and FALSE. These are the reserved keywords in R for representing logical true and false values, respectively.
In R, the ______ function can be used to get a summary of the data in a data frame.
- summary()
- describe()
- stats()
- overview()
The summary() function in R can be used to obtain a summary of the data in a data frame. It provides information such as minimum, maximum, median, mean, and quartiles for each column in the data frame.
How do you determine the length of a string in R?
- len()
- length()
- nchar()
- strlen()
In R, the nchar() function is used to determine the length of a string. For example, nchar("Hello") would return 5.
A comment in R starts with the symbol _________.
- #
- ##
- --
- //
In R, the '#' symbol is used to denote a comment. Any text following this symbol on a line is ignored by the R interpreter. This is a useful way to annotate your code.