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Multivariate Analysis: Discrimination and Classification

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Multivariate Analysis: Discrimination and Classification

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Questions and Answers

What is the main objective of transforming multivariate observations to univariate observations in Linear Discriminant Analysis?

To separate the new observations derived from population 1 and 2 as much as possible (correct)

To estimate the common covariance matrix

To predict the class of a given observation

To assume normality of the populations

What is the assumption about the population covariance matrices in Linear Discriminant Analysis?

They are linearly related

They are normally distributed

They are equal (correct)

They are unequal

What is the primary use of linear combinations of predictors in Linear Discriminant Analysis?

To predict the class of a given observation (correct)

To transform the data into a normal distribution

To identify the most important predictors

To estimate the population covariance matrices

What is the assumption about the predictor variables in Linear Discriminant Analysis?

They are normally distributed Signup and view all the answers

What is the purpose of checking the univariate distributions of each variable in Linear Discriminant Analysis?

To ensure that the predictors are normally distributed Signup and view all the answers

What is the purpose of transforming the predictor variables in Linear Discriminant Analysis?

To make the data normally distributed Signup and view all the answers

What is the effect of not removing outliers from the data in Linear Discriminant Analysis?

It increases the risk of biased estimates Signup and view all the answers

What is the purpose of standardizing the variables in Linear Discriminant Analysis?

To make the variables' scales comparable Signup and view all the answers

What is the primary direction of the Linear Discriminant Analysis algorithm?

To maximize the separation between classes Signup and view all the answers

What is the assumption about the classes in Linear Discriminant Analysis?

They have identical variances Signup and view all the answers