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Discriminant Analysis

Discriminant analysis is a statistical technique used to classify observations into two or more groups based on a set of predictor variables. It is often used in marketing, finance, and other fields where it is important to be able to predict the group to which an observation belongs.

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Questions

Question 1 Multiple Choice (Single Answer)

What is the purpose of discriminant analysis?

  1. To classify observations into two or more groups
  2. To predict the group to which an observation belongs
  3. To identify the most important predictor variables
  4. To reduce the number of predictor variables
Question 2 Multiple Choice (Single Answer)

What are the two main types of discriminant analysis?

  1. Linear discriminant analysis and quadratic discriminant analysis
  2. Stepwise discriminant analysis and forward selection discriminant analysis
  3. Canonical discriminant analysis and logistic discriminant analysis
  4. Discriminant function analysis and cluster analysis
Question 3 Multiple Choice (Single Answer)

What is the difference between linear discriminant analysis and quadratic discriminant analysis?

  1. Linear discriminant analysis assumes that the predictor variables are normally distributed, while quadratic discriminant analysis does not.
  2. Linear discriminant analysis is more robust to outliers than quadratic discriminant analysis.
  3. Linear discriminant analysis is more computationally efficient than quadratic discriminant analysis.
  4. All of the above
Question 4 Multiple Choice (Single Answer)

What are the steps involved in discriminant analysis?

  1. Select the predictor variables
  2. Transform the data if necessary
  3. Fit the discriminant function
  4. Classify the observations
  5. Evaluate the model
Question 5 Multiple Choice (Single Answer)

What are some of the applications of discriminant analysis?

  1. Marketing: To predict the likelihood that a customer will purchase a product
  2. Finance: To predict the risk of a loan applicant defaulting on a loan
  3. Healthcare: To predict the likelihood that a patient will develop a disease
  4. All of the above
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