Question 1

Which of the following is an example of a categorical independent variable?

Accepted Answer

A)  price 
B)  product amount 
C)  marital status 
D)  date of birth 
A)  price 
B)  product amount 
C)  marital status 
D)  date of birth

Question 2

Mean Absolute Error

Accepted Answer

A)  represents the difference between the observed and predicted value of the dependent variable. 
B)  is the percentage absolute difference the prediction is, on average, from the actual target. 
C)  measures the total difference between the predicted and actual values of the model. 
D)  indicates how different the residuals are from zero. 
A)  represents the difference between the observed and predicted value of the dependent variable. 
B)  is the percentage absolute difference the prediction is, on average, from the actual target. 
C)  measures the total difference between the predicted and actual values of the model. 
D)  indicates how different the residuals are from zero.

Question 3

In the ridesharing case study data dictionary, the rideshare variable refers to the name of ride sharing service (e.g., Lyft or Uber).

Accepted Answer

A) True 
 B)False

Question 4

A predictive model only uses coefficient sizes, goodness of fit, and overall model fit.

Accepted Answer

A) True 
 B)False

Question 5

A descriptive/explanatory model uses validation dataset metrics such as Mean Absolute Percentage Error and Root Mean Squared Error.

Accepted Answer

A) True 
 B)False

Question 6

Explain how the quality of a predictive model is determined using metrics.

Accepted Answer

The quality of a predictive model is det

Question 7

Overfitting happens when sample characteristics are included in the regression model that can be generalized to new data.

Accepted Answer

A) True 
 B)False

Question 8

Describe how the Ordinary least squares (OLS) method minimizes the sum of squared errors.

Accepted Answer

The Ordinary Least Squares (OLS) method

Question 9

Which of the following metrics returns the percentage absolute difference in error prediction, on average, from the actual target?

Accepted Answer

A)  Mean Absolute Percentage Error 
B)  Mean Absolute Error 
C)  precipProbability 
D)  Root Mean Squared Error 
A)  Mean Absolute Percentage Error 
B)  Mean Absolute Error 
C)  precipProbability 
D)  Root Mean Squared Error

Question 10

In feature selection, ________ starts with a regression model that includes all predictors under consideration.

Accepted Answer

A)  backward elimination 
B)  forward selection 
C)  overfitting 
D)  stepwise selection 
A)  backward elimination 
B)  forward selection 
C)  overfitting 
D)  stepwise selection

Question 11

Employment status (unemployed, employed, student, retired) is an example of a dichotomous value.

Accepted Answer

A) True 
 B)False

Question 12

________ is used to determine whether two or more independent variables are good predictors of the single target variable.

Accepted Answer

A)  Explanatory modeling 
B)  Multiple regression 
C)  Predictive modeling 
D)  The Ordinary least squares method 
A)  Explanatory modeling 
B)  Multiple regression 
C)  Predictive modeling 
D)  The Ordinary least squares method

Question 13

Which of the following is true of the hold-out method of model validation?

Accepted Answer

A)  This procedure cannot be used in advanced analytics techniques due to its complexity. 
B)  Two-thirds of the data is randomly selected and removed to build the regression model. 
C)  This method uses the training dataset and is validated using the single selected validation set. 
D)  This method requires no training time and a minimum of computer processing power. 
A)  This procedure cannot be used in advanced analytics techniques due to its complexity. 
B)  Two-thirds of the data is randomly selected and removed to build the regression model. 
C)  This method uses the training dataset and is validated using the single selected validation set. 
D)  This method requires no training time and a minimum of computer processing power.

Question 14

Identify a difference between the model evaluation methods of hold-out variation and N-fold cross validation.

Accepted Answer

A)  Unlike the N-fold cross validation method, the hold-out variation method requires high amounts of training time and computer processing power. 
B)  Unlike in the hold-out variation method, the N-fold cross validation method randomly selects one set of two-thirds of data to build the regression model. 
C)  Unlike the N-fold cross validation method, the hold-out variation method divides data into many smaller subsets. 
D)  Unlike the hold-out sample method, the N-fold cross validation method is less sensitive to variation in training and validation datasets selection. 
A)  Unlike the N-fold cross validation method, the hold-out variation method requires high amounts of training time and computer processing power. 
B)  Unlike in the hold-out variation method, the N-fold cross validation method randomly selects one set of two-thirds of data to build the regression model. 
C)  Unlike the N-fold cross validation method, the hold-out variation method divides data into many smaller subsets. 
D)  Unlike the hold-out sample method, the N-fold cross validation method is less sensitive to variation in training and validation datasets selection.

Question 15

With the accuracy measures of Mean Absolute Error, Mean Absolute Percentage Error, and Root Mean Squared Error, lower values indicate a better fit.

Accepted Answer

A) True 
 B)False

Question 16

In the ridesharing case study, the windspeed variable refers to the

Accepted Answer

A)  the likelihood of rain for a specific forecast period and location. 
B)  wind speed at the time and location of the ride. 
C)  wind gust measuring the increase in wind speed at the time and location of the ride. 
D)  air quality at the time and location of the ride. 
A)  the likelihood of rain for a specific forecast period and location. 
B)  wind speed at the time and location of the ride. 
C)  wind gust measuring the increase in wind speed at the time and location of the ride. 
D)  air quality at the time and location of the ride.

Which of the following is an example of a categorical independent variable?

Mean Absolute Error

In the ridesharing case study data dictionary, the rideshare variable refers to the name of ride sharing service (e.g., Lyft or Uber).

A predictive model only uses coefficient sizes, goodness of fit, and overall model fit.

A descriptive/explanatory model uses validation dataset metrics such as Mean Absolute Percentage Error and Root Mean Squared Error.

Explain how the quality of a predictive model is determined using metrics.

Overfitting happens when sample characteristics are included in the regression model that can be generalized to new data.

Describe how the Ordinary least squares (OLS) method minimizes the sum of squared errors.

Which of the following metrics returns the percentage absolute difference in error prediction, on average, from the actual target?

In feature selection, ________ starts with a regression model that includes all predictors under consideration.

Employment status (unemployed, employed, student, retired) is an example of a dichotomous value.

________ is used to determine whether two or more independent variables are good predictors of the single target variable.

Which of the following is true of the hold-out method of model validation?

Identify a difference between the model evaluation methods of hold-out variation and N-fold cross validation.

With the accuracy measures of Mean Absolute Error, Mean Absolute Percentage Error, and Root Mean Squared Error, lower values indicate a better fit.

In the ridesharing case study, the windspeed variable refers to the

Introduction to Marketing Analytics

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Exam 5: Regression Analysis

Which of the following is an example of a categorical independent variable?

Mean Absolute Error

In the ridesharing case study data dictionary, the rideshare variable refers to the name of ride sharing service (e.g., Lyft or Uber).

A predictive model only uses coefficient sizes, goodness of fit, and overall model fit.

A descriptive/explanatory model uses validation dataset metrics such as Mean Absolute Percentage Error and Root Mean Squared Error.

Explain how the quality of a predictive model is determined using metrics.

Overfitting happens when sample characteristics are included in the regression model that can be generalized to new data.

Describe how the Ordinary least squares (OLS) method minimizes the sum of squared errors.

Which of the following metrics returns the percentage absolute difference in error prediction, on average, from the actual target?

In feature selection, ________ starts with a regression model that includes all predictors under consideration.

Employment status (unemployed, employed, student, retired) is an example of a dichotomous value.

________ is used to determine whether two or more independent variables are good predictors of the single target variable.

Which of the following is true of the hold-out method of model validation?

Identify a difference between the model evaluation methods of hold-out variation and N-fold cross validation.

With the accuracy measures of Mean Absolute Error, Mean Absolute Percentage Error, and Root Mean Squared Error, lower values indicate a better fit.

In the ridesharing case study, the windspeed variable refers to the

Introduction to Marketing Analytics

Data Management

Exploratory Data Analysis Using Cognitive Analytics

Data Visualization

Neural Networks

Automated Machine Learning

Cluster Analysis

Market Basket Analysis

Natural Language Processing - Text Mining and Sentiment Analysis

Social Network Analysis

Web Analytics

Filters