Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
1) How is the line of best fit determined in linear regression?
A) Choose parameters that minimize the sum of squared errors of the predictions to the
data, and minimize the linear deviance.
B) Choose parameters that minimize the logistic regression and maximize sum of the
residuals.
C) Choose parameters that minimize the deviance of the logistic model.
D) Choose parameters that maximize the residuals and the linear deviance.
2) In linear regression, how should the chosen parameters affect the linear deviance?
A) They should minimize it.
B) They should maximize it.
C) They should make it equal the residuals.
D) They should reflect and make it equal the logistic regression.
3) In linear regression, how should the chosen parameters affect the sum of squared errors?
A) They should minimize it.
B) They should maximize it.
C) They should make it equal the residuals.
D) They should reflect and make it equal the logistic regression.
4) How is the line of best fit determined in logistic regression?
A) Choose parameters that minimize the deviance of the logistic model.
B) Choose parameters that maximize the residuals of the logistic model.
C) Choose parameters that maximize the deviance of the logistic model.
D) Choose parameters that minimize the residuals and the linear distance.
5) What is the residual deviance?
A) The sum of squared errors
B) The parameters used in linear regression
C) The parameters used in logistic regression
D) The mean linear deviance
6) What is the purpose of transforming data prior to running a linear regression?
A) To fit the data to the assumptions of the linear model
B) To determine the assumptions of the linear model
C) To ensure the response is binary
D) To use an additive relationship between x and y
1
,Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
7) Imagine that you are transforming data to run a linear regression. What type of relationship
between variables should utilize a log transform on the response?
A) Multiplicative
B) Binary
C) Additive
D) Residual
8) Which of the following are the assumptions made when fitting a linear regression model?
Note: Select all that apply.
A) Independent observations
B) Normally distributed residuals
C) Categorical response variables
D) Organic elasticity
E) Lower deviance than in a logistic model
9) Which of the following are the assumptions made when fitting a linear regression model?
Note: Select all that apply.
A) Constant error variance of the residuals across x
B) Normally distributed residuals
C) Dependent observations
D) Logarithmically distributed residuals
E) Variable error of the residuals across x
10) Which of the following are the assumptions made when fitting a linear regression model
under the conditions εi ~ N(0, σ2)?
Note: Select all that apply.
A) Independent observations
B) Normally distributed residuals
C) Constant error variance of the residuals across x
D) Variable error variance of the sum of square errors
E) An exponential relationship between x and y
2
,Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
11) What is the fundamental difference between linear and logistic regression?
A) The response variable in linear regression is continuous, while in logistic regression it
is binary.
B) The response variable in linear regression is binary, while in logistic regression it is
quantitative.
C) Residuals in linear regression are quantitative, while in logistic regression they are
categorical.
D) The accuracy of linear regression is high, while that of logistic regression is low.
12) What best describes the response variable in linear regression?
A) The response variable is continuous.
B) The response variable is categorical.
C) The response variable is binary.
D) The response variable is qualitative.
13) What best describes the response variable in logistic regression?
A) The response variable is binary.
B) The response variable is quantitative.
C) The response variable is numeric.
D) The response variable is continuous.
3
, Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
14) Load the dataavocado.csv. The data includes sales, price, and type (conventional or organic).
For this problem, we will ignore the panel nature of the data and treat Total.volume as sales.
What does a scatter plot of log(sales) versus log(price) colored by type look like?
A)
4
Chapter 01 - Static
1) How is the line of best fit determined in linear regression?
A) Choose parameters that minimize the sum of squared errors of the predictions to the
data, and minimize the linear deviance.
B) Choose parameters that minimize the logistic regression and maximize sum of the
residuals.
C) Choose parameters that minimize the deviance of the logistic model.
D) Choose parameters that maximize the residuals and the linear deviance.
2) In linear regression, how should the chosen parameters affect the linear deviance?
A) They should minimize it.
B) They should maximize it.
C) They should make it equal the residuals.
D) They should reflect and make it equal the logistic regression.
3) In linear regression, how should the chosen parameters affect the sum of squared errors?
A) They should minimize it.
B) They should maximize it.
C) They should make it equal the residuals.
D) They should reflect and make it equal the logistic regression.
4) How is the line of best fit determined in logistic regression?
A) Choose parameters that minimize the deviance of the logistic model.
B) Choose parameters that maximize the residuals of the logistic model.
C) Choose parameters that maximize the deviance of the logistic model.
D) Choose parameters that minimize the residuals and the linear distance.
5) What is the residual deviance?
A) The sum of squared errors
B) The parameters used in linear regression
C) The parameters used in logistic regression
D) The mean linear deviance
6) What is the purpose of transforming data prior to running a linear regression?
A) To fit the data to the assumptions of the linear model
B) To determine the assumptions of the linear model
C) To ensure the response is binary
D) To use an additive relationship between x and y
1
,Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
7) Imagine that you are transforming data to run a linear regression. What type of relationship
between variables should utilize a log transform on the response?
A) Multiplicative
B) Binary
C) Additive
D) Residual
8) Which of the following are the assumptions made when fitting a linear regression model?
Note: Select all that apply.
A) Independent observations
B) Normally distributed residuals
C) Categorical response variables
D) Organic elasticity
E) Lower deviance than in a logistic model
9) Which of the following are the assumptions made when fitting a linear regression model?
Note: Select all that apply.
A) Constant error variance of the residuals across x
B) Normally distributed residuals
C) Dependent observations
D) Logarithmically distributed residuals
E) Variable error of the residuals across x
10) Which of the following are the assumptions made when fitting a linear regression model
under the conditions εi ~ N(0, σ2)?
Note: Select all that apply.
A) Independent observations
B) Normally distributed residuals
C) Constant error variance of the residuals across x
D) Variable error variance of the sum of square errors
E) An exponential relationship between x and y
2
,Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
11) What is the fundamental difference between linear and logistic regression?
A) The response variable in linear regression is continuous, while in logistic regression it
is binary.
B) The response variable in linear regression is binary, while in logistic regression it is
quantitative.
C) Residuals in linear regression are quantitative, while in logistic regression they are
categorical.
D) The accuracy of linear regression is high, while that of logistic regression is low.
12) What best describes the response variable in linear regression?
A) The response variable is continuous.
B) The response variable is categorical.
C) The response variable is binary.
D) The response variable is qualitative.
13) What best describes the response variable in logistic regression?
A) The response variable is binary.
B) The response variable is quantitative.
C) The response variable is numeric.
D) The response variable is continuous.
3
, Test Bank For Modern Business Analytics, 1st Edition
Chapter 01 - Static
14) Load the dataavocado.csv. The data includes sales, price, and type (conventional or organic).
For this problem, we will ignore the panel nature of the data and treat Total.volume as sales.
What does a scatter plot of log(sales) versus log(price) colored by type look like?
A)
4
