3003 Week 8 Practice Quiz

3003 Week 8 Practice Quiz

University

13 Qs

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3003 Week 8 Practice Quiz

3003 Week 8 Practice Quiz

Assessment

Quiz

Science

University

Practice Problem

Medium

Created by

Chloe Hurrell

Used 36+ times

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13 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary purpose of using multiple regression analysis?

To estimate a single mean response variable.

To predict the value of one dependent variable based on the values of multiple independent variables

To categorize data into distinct groups.

To calculate correlation coefficients between variables.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which assumption is not required in multiple regression analysis?

Independence of errors.

Normal distribution of variables.

Homoscedasticity of errors.

Equal variance across all levels of the independent variables.

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What does multicollinearity refer to in the context of multiple regression?

Correlation between error terms.

A linear relationship between two or more independent variables.

Correlation between the dependent and independent variables.

The variance of the regression coefficients.

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the context of regression diagnostics, what is the purpose of a residual plot?

To display the actual vs. predicted values of the dependent variable.

To identify potential outliers in the data.

To check the linearity and homoscedasticity of residuals.

To compare different regression models.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is an indication of a well-fitting regression model?

High R-squared value.

High standard error.

Presence of multicollinearity.

Presence of heteroscedasticity.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the implication of heteroscedasticity in a regression model?

Increased standard errors of the coefficients, leading to less reliable statistical tests.

Improved accuracy of the predictions.

Reduced multicollinearity among predictors.

Increased R-squared value.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Why might a researcher decide to apply a transformation to a variable in regression analysis?

To make the data less understandable.

To increase the multicollinearity between predictors.

To make the data distribution more normal or stabilize variance, improving the validity of statistical tests.

To reduce the computational speed of the analysis.

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