STUDY GUIDE ISYE 6414
Well Written Answers & Rationales
Practice Midterm Exam 1
Closed Book Section
Part 1 (from F23)
,This is the Practice Midterm Exam 1. .
True or False
Question 1
pts
In Regression analysis, the response variable is a random variable because it varies
with changes in the predicting variable(s).
True
False
Check Module 1 Topic 1.1 Lesson 1
Response Variable: It is a Random Variable. It varies with changes in the predictor/s
along with other random changes.
Predicting Variable: It is a Fixed Variable. It does not change with the response, but it is
set fixed before the response is measured.
Question 2
pts
In Linear Regression, the sampling distribution of the variance estimator ( �^2) or
MSE, is a t-distribution with n degrees of freedom.
True
False
Check Module 1.2 Slide 13
False, the sampling distribution of the Mean Squared Error, or variance estimator, is a
chi-square distribution with n-2 degrees of freedom.
Question 3
pts
ANOVA is an example of a linear regression model where the predicting factor is a
categorical or qualitative variable.
, True
False
Module 1 Lesson 1.7 - Slide 10
Basics of ANOVA
Question 4
pts
If any of the Linear Regression assumptions do not hold, then we interpret this to mean
linear regression is not useful for modeling the data.
True
False
Module 1 Lesson 1.5 Assumptions - slide 11
Failing an assumption does not mean we disregard a linear model completely. Linear
regression can still be useful because we can transform our predicting variable to
improve the linear assumption.
Question 5
pts
In calculating the degrees of freedom for the Pooled Variance Estimator (��2), we use
�−�−1 degrees freedom. Where � is the number groups and � is the total number of
samples.
True
False
Check Module 1 Lesson 1.8 - slide 4
Well Written Answers & Rationales
Practice Midterm Exam 1
Closed Book Section
Part 1 (from F23)
,This is the Practice Midterm Exam 1. .
True or False
Question 1
pts
In Regression analysis, the response variable is a random variable because it varies
with changes in the predicting variable(s).
True
False
Check Module 1 Topic 1.1 Lesson 1
Response Variable: It is a Random Variable. It varies with changes in the predictor/s
along with other random changes.
Predicting Variable: It is a Fixed Variable. It does not change with the response, but it is
set fixed before the response is measured.
Question 2
pts
In Linear Regression, the sampling distribution of the variance estimator ( �^2) or
MSE, is a t-distribution with n degrees of freedom.
True
False
Check Module 1.2 Slide 13
False, the sampling distribution of the Mean Squared Error, or variance estimator, is a
chi-square distribution with n-2 degrees of freedom.
Question 3
pts
ANOVA is an example of a linear regression model where the predicting factor is a
categorical or qualitative variable.
, True
False
Module 1 Lesson 1.7 - Slide 10
Basics of ANOVA
Question 4
pts
If any of the Linear Regression assumptions do not hold, then we interpret this to mean
linear regression is not useful for modeling the data.
True
False
Module 1 Lesson 1.5 Assumptions - slide 11
Failing an assumption does not mean we disregard a linear model completely. Linear
regression can still be useful because we can transform our predicting variable to
improve the linear assumption.
Question 5
pts
In calculating the degrees of freedom for the Pooled Variance Estimator (��2), we use
�−�−1 degrees freedom. Where � is the number groups and � is the total number of
samples.
True
False
Check Module 1 Lesson 1.8 - slide 4
