LIR 832 - Lecture 4-handout - 3slides

LIR 832 - Lecture 4-handout - 3slides - Multivariate...

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1 Multivariate Methods LIR 832 February 13, 2007 Multivariate Methods: Topics of the Day A. Isolating Interventions in a multi-causal world B. Multivariate probability Distributions C. The Building Block: covariance D. The Next Step: Correlation A Multivariate World Isolating Interventions in a Multi-Causal World ± A. Example of problem: ² Evaluate a program to reduce absences from a plant? ² Is there age discrimination? ± B. Types of data ² Experimental ² Quasi-experimental ² Non-experimental ± C. Need multivariate analysis to sort out causal relationships.
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2 Bi-Variate Relations: A First Run at Multivariate Methods A. Many of the issues we are interested in are essentially about the relationship between two variables. B. Bi-variate can be generalized to multivariate relationships C. We learn bi-variate formally and make more intuitive reference to multivariate. D. What do we mean by bi-variate relationship? Bi-Variate Example Our firm, has formed teams of engineers, accountants and general managers at all plants to work on several issues that are considered important in the firm. The firm has long been committed to gender diversity and we are interested in the distribution of gender among our managerial classifications. We are particularly concerned about the distribution of gender on these teams and particularly among engineers. Consider the distribution of two statistics about these three person teams. ± a. gender of the team members (X: x = number of men) ± b. is the engineer a woman (Y: 0 = man, 1 = woman) Bi-Variate Example (cont.)
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3 Bi-Variate Example (cont.)
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4 Bi-Variate Example (cont.) We can also use this information to build conditional probabilities : What is the likelihood that the engineer is a woman, given that we have a man on the team?
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LIR 832 - Lecture 4-handout - 3slides - Multivariate...

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