R Programming Mock Test 7

10%

Question 1 of 10

1. The profiler can be turned off by passing _________ to Rprof().

NULL

Question 1 of 10

Question 2 of 10

2. What will be the output of the following R code?

> printmessage2 <- function(x) {
+                      if(is.na(x))
+                              print("x is a missing value!")
+                      else if(x > 0)
+                              print("x is greater than zero")
+                      else
+                              print("x is less than or equal to zero")
+                      invisible(x)
+ }
> printmessage2(NA)

"x is less than or equal to zero"

"x is a missing value!"

Error

"x is greater than zero"

Question 2 of 10

Question 3 of 10

3. The _______ function computes the time (in seconds) needed to execute an expression.

system.datetime()

system.timedeb()

system.time()

system.deb()

Question 3 of 10

Question 4 of 10

4. How many methods exist for normalizing the data?

three

profiler

one

two

Question 4 of 10

Question 5 of 10

5. What will be the output of the following R code?

> x <- rnorm(10)
> x

Error

[1] 0.01874617 -0.18425254 -1.37133055 -0.59916772 0.29454513
[6] 0.38979430 -1.20807618 -0.36367602 -1.62667268 -0.25647839

Min. 1st Qu. Median Mean 3rd Qu. Max.
18.09 19.75 21.22 20.74 21.77 22.20

[1] 22.20356 21.51156 19.52353 21.97489 21.48278 20.17869 18.09011
[8] 19.60970 21.85104 20.96596

Question 5 of 10

Question 6 of 10

6. Point out the wrong statement?

For each probability distribution there are typically four functions

r function is sufficient for simulating random numbers

For each probability distribution there are typically three functions

R comes with a set of pseudo-random number generators

Question 6 of 10

Question 7 of 10

7. R comes with a ________ to help you optimize your code and improve its performance.

debugger

monitor

browser

profiler

Question 7 of 10

Question 8 of 10

8. ________ generate random Normal variates with a given mean and standard deviation.

dnorm

rnorm

pnorm

rpois

Question 8 of 10

Question 9 of 10

9. Point out the wrong statement?

The sample() function draws randomly from a specified set of (scalar) objects allowing you to sample from arbitrary distributions of numbers

The sampling() function draws randomly from a specified set of objects

You should always set the random number seed when conducting a simulation

Drawing samples from specific probability distributions can be done with “s” functions

Question 9 of 10

Question 10 of 10

10. Point out the correct statement?

Sequence of operations is sometimes referred to as “map-reduce”

You can use tsplit() to evaluate a function single time each with a same argument

apply() can be thought of as a combination of split() and sapply() for vectors only

split() takes elements of the list and passes them as the first argument of the function you are applying

Question 10 of 10