Exam 17: Business Analytics

SCENARIO 17-6 The neural network output below was obtained for predicting the weekend box office revenue of a newly released movie (in thousands of dollars)based on data collected in different cities on the expenditure (at $25, $30, $35, $40, $45, $50, $55, $60 $65 or $70 thousands)spent on TV advertising and the number of times (10, 15, 20, 25, 30 or 35)a day the advertisement appear on TV. -Referring to Scenario 17-6, what is the r-square of model for the training data?

SCENARIO 17-2 The treemap below shows the amounts (size)measured in billions of US dollars and percentage changes from prior year (color)of business-to-consumer e-commerce sales last year for North America, Asia Pacific, Western Europe, Central & Eastern Europe, Latin America, and Middle East & Africa. -Referring to Scenario 17-2, the North America region has the fastest growth in business-to-consumer ecommerce sales last year.

The statistic is a measure of the probability that can be attributed to the response that has occurred.

SCENARIO 17-3 The tree diagram below shows the results of the classification tree model that has been constructed to predict the probability of a cable company's customers who will switch ("Yes" or "No")into its bundled program offering based on the price ($30, $40, $50, $60)and whether the customer spends more than 5 hours a day watching TV ("Yes" or "No")using the data set of 100 customers collected from a survey. -Referring to Scenario 17-3, the highest probability of switching is predicted to occur among customers who watch more than 5 hours of TV a day and are offered the bundled price of between $30 and $40.

SCENARIO 17-5 The output below shows the results of the neural network model that has been constructed to predict the probability of a cable company's customers who will switch ("Yes" or "No")into its bundled program offering based on the price ($30, $40, $50, $60)and whether the customer spends more than 5 hours a day watching TV ("Yes" or "No")using the data set of 100 customers collected from a survey. -Referring to Scenario 17-5, out of the 7 customers who did switch in the validation data set, how many are correctly classified by the neural network?

Which of the following is NOT one of the categories of predictive analytics methods?

SCENARIO 17-6 The neural network output below was obtained for predicting the weekend box office revenue of a newly released movie (in thousands of dollars)based on data collected in different cities on the expenditure (at $25, $30, $35, $40, $45, $50, $55, $60 $65 or $70 thousands)spent on TV advertising and the number of times (10, 15, 20, 25, 30 or 35)a day the advertisement appear on TV. -Referring to Scenario 17-6, what is the r-square of model for the validating data?

SCENARIO 17-5 The output below shows the results of the neural network model that has been constructed to predict the probability of a cable company's customers who will switch ("Yes" or "No")into its bundled program offering based on the price ($30, $40, $50, $60)and whether the customer spends more than 5 hours a day watching TV ("Yes" or "No")using the data set of 100 customers collected from a survey. -Referring to Scenario 17-5, the misclassification rate of 0.2058824 in the validation data set means that how many customers in the validation data are incorrectly classified?

Being able to monitor business activities in near real time is a feature most associated with:

SCENARIO 17-5 The output below shows the results of the neural network model that has been constructed to predict the probability of a cable company's customers who will switch ("Yes" or "No")into its bundled program offering based on the price ($30, $40, $50, $60)and whether the customer spends more than 5 hours a day watching TV ("Yes" or "No")using the data set of 100 customers collected from a survey. -Referring to Scenario 17-5, out of the 27 customers who did not switch in the validation data set, how many are correctly classified by the neural network?

Multilayer perceptrons usually contain an input layer, a hidden layer and an output layer.

There is no significant difference between filtering performed in a complex real-world business analytic and filtering performed using the slicers in a PivotTable in Excel.

Splitting of a node might be followed by pruning if necessary in a classification tree.

SCENARIO 17-7 The output below shows the results of cluster analysis on the different regions of the world (North America, Asia Pacific, Western Europe, Central & Eastern Europe, Latin America, and Middle East & Africa)based on the amounts (in billions of US dollars)and the percentage changes from prior year of business-to-consumer e-commerce sales last year. -Referring to Scenario 17-7, Middle East & Africa is the next region that clusters with the Central & Eastern Europe and Latin America cluster.

The prescriptive analytics technique in which the decision maker sets constraints that reflect resource limitations to determine how the process works most effectively is called simulation.

Neural networks use the validating data to uncover a model and then the training data to see if the model can make the correct prediction or classification.

Successful implementation of a regression tree requires rules for deciding when a branch of the tree cannot be split any more.

SCENARIO 17-3 The tree diagram below shows the results of the classification tree model that has been constructed to predict the probability of a cable company's customers who will switch ("Yes" or "No")into its bundled program offering based on the price ($30, $40, $50, $60)and whether the customer spends more than 5 hours a day watching TV ("Yes" or "No")using the data set of 100 customers collected from a survey. -Referring to Scenario 17-3, the highest probability of switching is predicted to occur among customers who watch more than 5 hours of TV a day and are offered the bundled price of higher than $40.

Bullet graphs that use color to represent the value of a second variable, thereby increasing the data density of the displays, is an example of chartjunk.

In a regression tree, the dependent variable is a categorical variable.