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Module 32: Multiple Regression

Module 32: Multiple Regression

Module 32: Multiple Regression. This module reviews simple linear regression and then discusses multiple regression. The next module contains several examples. Reviewed 19 July 05/MODULE 32. Module Content. Review of Simple Linear Regression Multiple Regression

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597 views • 46 slides
Module 32: Multiple Regression

Module 32: Multiple Regression

Module 32: Multiple Regression. This module reviews simple linear regression and then discusses multiple regression. The next module contains several examples. Reviewed 19 July 05/MODULE 32. Module Content. Review of Simple Linear Regression Multiple Regression

★ ★ ★ ★ ★

685 views • 46 slides
Module 32: Multiple Regression

Module 32: Multiple Regression

Module 32: Multiple Regression. This module reviews simple linear regression and then discusses multiple regression. The next module contains several examples. Reviewed 19 July 05/MODULE 32. Module Content. Review of Simple Linear Regression Multiple Regression

★ ★ ★ ★ ★

664 views • 46 slides
Logistic regression

Logistic regression

Logistic regression. A quick intro. Why Logistic Regression?. Big idea: dependent variable is a dichotomy (thought can use for more than 2 categories i.e. multinomial logistic regression) Why would we use?

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663 views • 23 slides
Decision making: Utility and assessing return on investment

Decision making: Utility and assessing return on investment

Decision making: Utility and assessing return on investment. Efficiency of linear models Alternative prediction models: multiple regression, multiple cut offs, multiple hurdle approaches Classical validity approach: selection ratio, base rate Decision-making accuracy

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968 views • 18 slides
Partial Least Squares

Partial Least Squares

Partial Least Squares. Very brief intro. Multivariate regression. The multiple regression approach creates a linear combination of the predictors that best correlates with the outcome

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3.47k views • 10 slides

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