Multiple Regression Analysis Quiz

Multiple Regression Analysis Quiz

University

15 Qs

quiz-placeholder

Similar activities

Hospitality and Service Excellent

Hospitality and Service Excellent

University

14 Qs

SOLIDWORKS Innovation Day - 2020

SOLIDWORKS Innovation Day - 2020

University

15 Qs

POM_Marketing Environment

POM_Marketing Environment

University

20 Qs

CHP 4: MARKET STRUCTURE

CHP 4: MARKET STRUCTURE

University

20 Qs

POM- Chapter 1

POM- Chapter 1

University

15 Qs

ABC2514 BUSINESS COMMUNICATION

ABC2514 BUSINESS COMMUNICATION

University

20 Qs

PARTNERSHIP LIQUIDATION

PARTNERSHIP LIQUIDATION

University

10 Qs

Multiple Regression Analysis Quiz

Multiple Regression Analysis Quiz

Assessment

Quiz

Business

University

Practice Problem

Hard

Created by

Sardor A'zam

Used 10+ times

FREE Resource

AI

Enhance your content in a minute

Add similar questions
Adjust reading levels
Convert to real-world scenario
Translate activity
More...

15 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

The multiple regression model does not allow us to examine the effects of individual independent variables on the dependent variable.

True

False

2.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

When we use OLS method, both parameters and variables need to be linear, otherwise we cannot use OLS method.

True

False

3.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

The method of OLS can be applied to estimate the multiple regression model.

True

False

4.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

R-squared is the proportion of the sample variation in the dependent variable explained by the independent variables, and it serves as a goodness-of-fit measure.

True

False

5.

MULTIPLE CHOICE QUESTION

20 sec • 1 pt

It is important to put too much weight on the value of R-squared when evaluating econometric models.

True

False

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Under the first four Gauss-Markov assumptions (MLR.1 through MLR.4), the OLS estimators are unbiased. This implies that including an irrelevant variable in a model has no effect on the unbiasedness of the intercept and other slope estimators. On the other hand, omitting a relevant variable causes OLS to be biased.

False

True

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

We use t statistics to test hypotheses about a single parameter against one- or two-sided alternatives, using one- or two-tailed tests, respectively. The most common null hypothesis is H0: bj = 0, but we sometimes want to test other values of bj under H0.

False

True

Access all questions and much more by creating a free account

Create resources

Host any resource

Get auto-graded reports

Google

Continue with Google

Email

Continue with Email

Classlink

Continue with Classlink

Clever

Continue with Clever

or continue with

Microsoft

Microsoft

Apple

Apple

Others

Others

Already have an account?