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Welcome to the Visualizing Data and Linear Regression MCQs Page

Dive deep into the fascinating world of Visualizing Data and Linear Regression with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Visualizing Data and Linear Regression, a crucial aspect of R Programming. In this section, you will encounter a diverse range of MCQs that cover various aspects of Visualizing Data and Linear Regression, 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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Check out the MCQs below to embark on an enriching journey through Visualizing Data and Linear Regression. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of R Programming.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Visualizing Data and Linear Regression. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Visualizing Data and Linear Regression MCQs | Page 2 of 7

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Q11.
Which of the following adds marginal sums to an existing table?

a.

par()

b.

prop.table()

c.

addmargins()

d.

quantile()

Discuss
Answer: (b).prop.table()
Q12.
Which of the following lists names of variables in a data.frame?

a.

quantile()

b.

names()

c.

barchart()

d.

par()

Discuss
Answer: (a).quantile()
Q13.
Which of the following is tool for chi-square distributions?

a.

pchisq()

b.

chisq()

c.

pnorm

d.

barchart()

Discuss
Answer: (c).pnorm
Q14.
Which of the following groups values of a variable into larger bins?

a.

cut

b.

col.max(x)

c.

stem

d.

which.max(x)

Discuss
Answer: (a).cut
Q15.
Which of the following determine the least-squares regression line?

a.

histo()

b.

lm

c.

barlm()

d.

col.max(x)

Discuss
Answer: (b).lm
Q16.
Which of the following is tool for checking normality?

a.

qqline()

b.

qline()

c.

anova()

d.

lm()

Discuss
Answer: (a).qqline()
Q17.
Which of the following is lattice command for producing boxplots?

a.

plot()

b.

bwplot()

c.

xyplot()

d.

barlm()

Discuss
Answer: (b).bwplot()
Q18.
Which of the following compute analysis of variance table for fitted model?

a.

ecdf()

b.

cum()

c.

anova()

d.

bwplot()

Discuss
Answer: (c).anova()
Q19.
Which of the following is used to find variance of all values?

a.

var()

b.

sd()

c.

mean()

d.

anova()

Discuss
Answer: (a).var()
Q20.
The purpose of fisher.test() is _______ test for contingency table.

a.

Chisq

b.

Fisher

c.

Prop

d.

Stem

Discuss
Answer: (b).Fisher
Page 2 of 7

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