Welcome to MCQss.com, your ultimate resource for MCQs on statistics with R. This page is designed to help you assess and enhance your understanding of statistical concepts, techniques, and analyses using the powerful R programming language.

Our MCQs cover a wide range of topics related to statistics with R. You will encounter questions on descriptive statistics, inferential statistics, hypothesis testing, regression analysis, analysis of variance, data visualization, and more. Each question presents a scenario or problem, and you are required to select the most appropriate answer from the given options.

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Deepen your understanding of statistics with R by engaging with the MCQs now. Strengthen your statistical knowledge, gain confidence in R programming, and unlock the full potential of statistics in your data analysis endeavors.

A. sum()

B. mean()

C. median()

D. sd()

A. read.xlsx()

B. read.table()

C. read.csv()

D. read.csv2()

A. rnorm()

B. runif()

C. rpois()

D. rexp()

A. To convert strings to numeric values

B. To calculate the standard deviation of a dataset

C. To display the structure of an R object, including its data type and dimensions

D. To transform a dataset into a matrix

A. ggplot2

B. dplyr

C. tidyr

D. reshape2

A. install()

B. install.package()

C. install.packages()

D. library()

A. cor()

B. cov()

C. sd()

D. var()

A. To sort a dataset in ascending order

B. To calculate the cumulative sum of a vector

C. To select specific rows or columns from a dataset based on certain conditions

D. To merge two datasets together

A. plot(y ~ x)

B. scatterplot(y, x)

C. ggplot(y, x) + geom_point()

D. boxplot(y, x)

A. To perform a chi-square test for independence

B. To calculate the mean of a dataset

C. To conduct a t-test to compare the means of two groups

D. To fit a linear regression model