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Question 1

What is produced at the end of this snippet of R code?

set.seed(1) rpois(5, 2) Answer

A vector with the numbers 1, 1, 2, 4, 1

Explanation

Because the 'set.seed()' function is used, 'rpois()' will always output the same vector in this code.

set.seed(1) rpois(5, 2) [1] 1 1 2 4 1 Question 2

What R function can be used to generate standard Normal random variables?

Answer

rnorm

Explanation

Functions beginning with the 'r' prefix are used to simulate random variates.

Standard probability distributions in R have a set of four functions that can be used to simulate variates, evaluate the density, evaluate the cumulative density, and evaluate the quantile function.

Question 3

When simulating data, why is using the set.seed() function important?

Answer

It ensures that the sequence of random numbers starts in a specific place and is therefore reproducible.

Question 4

Which function can be used to evaluate the inverse cumulative distribution function for the Poisson distribution?

Answer

qpois

Explanation

Probability distribution functions beginning with the 'q' prefix are used to evaluate the quantile function.

Question 5

What does the following code do?

set.seed(10) x <- rbinom(10, 10, 0.5) e <- rnorm(10, 0, 20) y <- 0.5 + 2 * x + e Answer

Generate data from a Normal linear model

Question 6

What R function can be used to generate Binomial random variables?

Answer

rbinom

Question 7

What aspect of the R runtime does the profiler keep track of when an R expression is evaluated?

Answer

the function call stack

Question 8

Consider the following R code

library(datasets) Rprof() fit <- lm(y ~ x1 + x2) Rprof(NULL) (Assume that y, x1, and x2 are present in the workspace.) Without running the code, what percentage of the run time is spent in the 'lm' function, based on the 'by.total' method of normalization shown in 'summaryRprof()'?

Answer

100%

Explanation

When using 'by.total' normalization, the top-level function (in this case, `lm()') always takes 100% of the time.

Question 9

When using 'system.time()', what is the user time?

Answer

It is the time spent by the CPU evaluating an expression

Question 10

If a computer has more than one available processor and R is able to take advantage of that, then which of the following is true when using 'system.time()'?

Answer

elapsed time may be smaller than user time