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Linear Regression

Total questions: 10

Worksheet time: 10mins

Name
Class
Date
1.

dependent variable is _________ for linear regression

a)

Categorical

b)

Continuous

c)

Continuous or categorical

d)

Ordinal

2.

Linear regression assumes dependent variable as_______ distributed

a)

Normally

b)

Skewed

c)

Binomially

d)

Polynomially

3.

LS stands for

a)

Last Square

b)

Least Sum

c)

Least Square

d)

Least Sum

4.

There are generally ________ number of points below [than ]above regression line.

a)

higher

b)

lower

c)

skewed

d)

equal

5.

The concept of independent variable depends on independent variable is called as _____.

a)

Multi-collinearity

b)

Auto-collinearity

c)

Duel-Collinearity

d)

By-Collinearity

6.

Multiple linear regression has more ________ variables.

a)

Symmetric

b)

Categorical

c)

Independent

d)

dependent

7.

classification is ______________ algorithm

a)

Supervised

b)

Semi-supervised

c)

Unsupervised

d)

Reinforcement

8.

Clusters minimize _____ distance and maximize _______ distance.

a)

Inter cluster, intra cluster

b)

intra cluster, inter cluster

c)

Intra cluster, overall

d)

overall , inter cluster

9.

Recommendation are example of ______ learning

a)

Supervised

b)

Unsupervised

c)

Semi-supervised

d)

Regression

10.

b0 is represented as ________

a)

Coefficient

b)

X intercept

c)

Y intercept

d)

error