# Welcome to the Distributions and Graphics in R programming MCQs Page

Dive deep into the fascinating world of Distributions and Graphics in R programming with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Distributions and Graphics in R programming, a crucial aspect of R Programming. In this section, you will encounter a diverse range of MCQs that cover various aspects of Distributions and Graphics in R programming, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within R Programming.

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### Distributions and Graphics in R programming MCQs | Page 1 of 6

Q1.
The _______ and ________ of a discrete random variable is easy to compute at the console.
Answer: (a).Mean, Variance
Q2.
Which of the following simple the square root of σ square?
Answer: (b).Standard deviation
Q3.
The abbreviation of Cumulative Distributive Function is ________
Answer: (d).CDF
Q4.
Which function is used to simulate discrete uniform random variables?
Answer: (a).Sample
Q5.
The binomial distribution is based on _______ trial.
Answer: (b).Bernoulli
Q6.
The corresponding R function for the PMF is __________
Answer: (c).Dbinom
Q7.
The corresponding R function for the CDF is __________
Answer: (b).Pbinom
Q8.
Random variables defined via the _______ package.
Answer: (c).Distr
Q9.
MGF means _____________
Answer: (c).Moment Generating Functions
Q10.
The empirical cumulative distribution function can be called as __________
Answer: (c).ECDF
Page 1 of 6

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