Which will test the hypothesis that two independent Normally distributed random variables A and B have different means?

Given the command: Z <- array(h, dim=c(3,4,2)), Z[1:24] stands for:

Given this named vector "X": > X <- c( 5, 10, 1, 20 ); > names( X ) <- c( "a", "b", "c", "d" ); Which operation is valid to show the 2nd and 4th components of X?

All of the following will directly display the help file for the plot() function except:

What R function can be used to tabulate values of categorical variable Y (columns) by categorical variable X (rows), including missing values?

Which R code subsets a matrix Y to only those records (rows) where a variable x (in Y) is less than 100?

What is the output for the command: > is.na( NaN ) ?

Suppose X is the vector c(1:10). Which R code will swap the values of the 3rd element of X and the 7th element of X?

Let X be a 3x4 matrix with non-zero values. The result of: > apply(X, 2, mean), is:

Which is NOT a valid R function for obtaining the residuals from a simple linear regression model of X predicting Y?

I want to use the sort() function, and I see in the help file that I my sort "an R object with a class, or a numeric, complex, character, or logical vector." Given this guidance, which is a valid call to sort()?