To calculate the mean of each row in a matrix in R, you would use the ______ function.
- rowMeans()
- colMeans()
- mean()
- apply()
To calculate the mean of each row in a matrix in R, you would use the rowMeans() function. The rowMeans() function computes the mean values across each row of the matrix.
In R, the ______ function can be used to create a scatter plot with a smooth line fitted to the data.
- scatterplot()
- smoothplot()
- lines()
- loess()
The loess() function in R can be used to fit a smooth line to a scatter plot. It uses the locally weighted scatterplot smoothing technique to estimate a smooth curve that captures the general trend in the data.
Which operator is used to assign a value to a variable in R?
- ->
- <-
- =
- All of the above
The '<-' operator is commonly used in R for assignment, although the '=' operator can also be used. However, '<-' is generally preferred because it makes the code more readable and avoids confusion with the '=' operator used for passing arguments to functions.
Suppose you're given a numeric vector in R and asked to calculate its mode. How would you do it?
- Use a custom function that counts frequencies and identifies the most frequent value
- Use the mode() function directly on the numeric vector
- Use the median() function to determine the central value
- Use the max() function to find the maximum value
To calculate the mode of a numeric vector in R, you would use a custom function that counts the frequencies of values and identifies the most frequent value(s) as the mode(s).
How do you create an array in R?
- Using the array() function
- Using the matrix() function
- Using the list() function
- Using the data.frame() function
In R, an array is created using the array() function. The array() function allows you to specify the values of the array, the dimensions, and other parameters such as dimension names. You can pass a vector of values and specify the dimensions to create the desired array structure.
Describe a situation where you would prefer to use paste0() over paste() in R.
- None of the above
- When you want to concatenate a large number of strings
- When you want to concatenate strings with a separator
- When you want to concatenate strings without a separator
You would prefer to use 'paste0()' over 'paste()' in R when you want to concatenate strings without a separator. The 'paste0()' function is a variation of the 'paste()' function that does not include a separator by default.
In R, to prematurely exit a for loop, you can use the ______ keyword.
- Next
- Skip
- Break
- Exit
In R, the break keyword is used to prematurely exit a for loop. When encountered, the break statement immediately terminates the loop and execution continues with the next statement after the loop.
In R, the ______ function can be used to check if an object is a matrix.
- is.matrix()
- is.vector()
- is.data.frame()
- is.array()
In R, the is.matrix() function can be used to check if an object is a matrix. It returns TRUE if the object is a matrix and FALSE otherwise. This function is useful for verifying the type of an object before applying operations specific to matrices.
How would you find the max or min value in each column or row of a matrix or data frame in R?
- Use the apply() function with the appropriate margin argument
- Use the max() or min() function with the appropriate argument
- Use the colMax() or rowMax() function for matrices
- Use the max.col() or min.col() function for data frames
To find the max or min value in each column or row of a matrix or data frame in R, you can use the apply() function. By specifying the appropriate margin argument (1 for rows, 2 for columns), you can apply the max() or min() function across the specified dimension.
Imagine you're asked to optimize a slow-running for loop in R. What are some strategies you could use to improve its performance?
- Use vectorized operations
- Preallocate output objects
- Minimize unnecessary calculations inside the loop
- All of the above
To optimize a slow-running for loop in R, you can use strategies such as converting the loop to vectorized operations when possible, preallocating output objects to reduce memory reallocation, and minimizing unnecessary calculations or redundant checks inside the loop. These strategies can significantly improve the performance of the loop.