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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 5 of 7

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Q41.
Analysis of variance in short form is?

a.

ANOV

b.

AVA

c.

ANOVA

d.

ANVA

Discuss
Answer: (c).ANOVA
Q42.
________ is a simple approach to supervised learning. It assumes that the dependence of Y on X1, X2, . . . Xp is linear.

a.

Linear regression

b.

Logistic regression

c.

Gradient Descent

d.

Greedy algorithms

Discuss
Answer: (a).Linear regression
Q43.
Although it may seem overly simplistic, _______ is extremely useful both conceptually and practically.

a.

Linear regression

b.

Logistic regression

c.

Gradient Descent

d.

Greedy algorithms

Discuss
Answer: (a).Linear regression
Q44.
When there are more than one independent variables in the model, then the linear model is termed as _______

a.

Unimodal

b.

Multiple model

c.

Multiple Linear model

d.

Multiple Logistic model

Discuss
Answer: (c).Multiple Linear model
Q45.
The parameter β0 is termed as intercept term and the parameter β1 is termed as slope parameter. These parameters are usually called as _________

a.

Regressionists

b.

Coefficients

c.

Regressive

d.

Regression coefficients

Discuss
Answer: (d).Regression coefficients
Q46.
The sum of squares of the difference between the observations and the line in the horizontal direction in the scatter diagram can be minimized to obtain the estimates is generally called?

a.

reverse regression method

b.

formal regression

c.

logistic regression

d.

simple regression

Discuss
Answer: (a).reverse regression method
Q47.
______ regression method is also known as the ordinary least squares estimation.

a.

Simple

b.

Direct

c.

Indirect

d.

Mutual

Discuss
Answer: (b).Direct
Q48.
__________ refers to a group of techniques for fitting and studying the straight-line relationship between two variables.

a.

Linear regression

b.

Logistic regression

c.

Gradient Descent

d.

Greedy algorithms

Discuss
Answer: (a).Linear regression
Q49.
In order to calculate confidence intervals and hypothesis tests, it is assumed that the errors are independent and normally distributed with mean zero and _______

a.

Mean

b.

Variance

c.

SD

d.

KNN

Discuss
Answer: (b).Variance
Q50.
What do we do the curvilinear relationship in linear regression?

a.

consider

b.

ignore

c.

may be considered

d.

sometimes consider

Discuss
Answer: (b).ignore
Page 5 of 7

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