Linear Regression

Linear Regression

University

5 Qs

quiz-placeholder

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Linear Regression

Linear Regression

Assessment

Quiz

Education

University

Practice Problem

Medium

Created by

Angeline Lydia

Used 3+ times

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5 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the slope coefficient(β1​) represent in a simple linear regression model?

The value of the dependent variable when the independent variable is zero.

The change in the dependent variable for a one-unit change in the independent variable.

The error term capturing the variability in the dependent variable.

The constant variance assumed in the error term.


2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In a simple linear regression model, what does the intercept coefficient (β0​) represent?

The change in the dependent variable for a one-unit change in the independent variable

The value of the dependent variable when the independent variable is zero.

The variability in the dependent variable that is not explained by the linear relationship

The constant variance assumed in the error term.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does the error term (ϵ) represent in a linear regression model?

The change in the dependent variable for a one-unit change in the independent variable.

The value of the dependent variable when the independent variable is zero.

The discrepancy between the observed values of the dependent variable and the values predicted by the regression model.

The variability in the dependent variable that is explained by the linear relationship.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What method is commonly used to estimate the coefficients in a linear regression model?

Maximum likelihood estimation

Bayesian estimation

Method of least squares

Gradient descent optimization

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In a multiple linear regression model, what does each coefficient represent?

The change in the dependent variable for a one-unit change in the corresponding independent variable, holding other variables constant.

The value of the dependent variable when all independent variables are zero.

The variability in the dependent variable that is not explained by the linear relationship.

The constant variance assumed in the error term.

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