Explore topic-wise MCQs in R Programming.

This section includes 8 Mcqs, each offering curated multiple-choice questions to sharpen your R Programming knowledge and support exam preparation. Choose a topic below to get started.

1.

Which of the following produces the variance covariance matrix?

A. sd(x, na.rm=TRUE)
B. mad(x, na.rm=TRUE)
C. fivenum(x, na.rm=TRUE)
D. var(x, na.rm=TRUE)
Answer» E.
Discussion
2.

Which of the following finds the maximum value in the vector x, exclude missing values?

A. rm(x)
B. max(x, na.rm=TRUE)
C. all(x)
D. x%in%y
Answer» C. all(x)
Discussion
3.

Which of the following tests each element of x for membership in y?

A. y%in%x
B. all(x)
C. any(x)
D. x%in%y
Answer» E.
Discussion
4.

Which of the following truncates real x to integers?

A. as.order(x)
B. as.integer(x)
C. as.numeric(x)
D. as.character(x)
Answer» C. as.numeric(x)
Discussion
5.

Which of the following is uniform distribution?

A. dunif(x, min=0, max=1, log = FALSE)
B. punif(q, min=0, max=1, lower.tail = TRUE, log.p = FALSE)
C. qunif(p, min=0, max=1, lower.tail = TRUE, log.p = FALSE)
D. runif(n, min=0, max=1)
Answer» B. punif(q, min=0, max=1, lower.tail = TRUE, log.p = FALSE)
Discussion
6.

which of the following statement gives cumulative sum?

A. cumsum(x,na=rm=TRUE)
B. cumprod(x)
C. cummax(x)
D. cummin(x)
Answer» B. cumprod(x)
Discussion
7.

Which of the following statement is normal distribution?

A. dnorm(x, mean=0, sd=1, log = FALSE)
B. pnorm(q, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE)
C. qnorm(p, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE)
D. rnorm(n, mean=0, sd=1)
Answer» B. pnorm(q, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE)
Discussion
8.

Which of the following statement find cases with no missing values?

A. complete <- subset(data.df,complete.cases(data.df)
B. complete <- sub(data.df,complete.cases(data.df)
C. complete <- subset(data.df,completeall.cases(data.df)
D. new <- old[n1:n2,n3:n4]
E.
Answer» B. complete <- sub(data.df,complete.cases(data.df)
Discussion