# Multiple Regression

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Multiple Regression

Introduction to Linear Multiple Regression

One of the goals of science is prediction: given a current state of affairs, researchers should be able to predict some future outcome. Imagine a situation where you want to assess how perceived corporate climate predicts company profit. It would be very useful to be able to explain the strength of the relationship between corporate climate and earnings and just how much of the variability in corporate climate explains in profit. Such information could be quite valuable in deciding financial resources to invest in changing corporate climate. The simple linear regression offers a technique through which to examine such a relationship.
This week, you will learn how to work with simple linear regression.
Learning Outcomes
By the end of this week, you will be able to (for ANCOVA):
? State underlying assumptions
? Determine whether assumptions have been met
? Propose alternatives if assumptions are not met
? State null and alternative hypotheses
? Analyze data using PASW
? Interpret and report the results with PASW, including effect size
? Describe sample size
? Report results in APA format
? Critique published work reporting on quantitative research
? Course Text: Discovering Statistics Using SPSS
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o Chapter 7, “Regression” (pp. 197-209)

Sections 7.1?7.4 provide an introduction to regression, including an explanation of how to do a simple regression on SPSS and how to interpret a simple regression.
? Handout: Journal Article Critique (Word document)

This handout explains the importance of scholarly critique and provides instructions for the journal article critique you will complete in this week’s Application 2 Assignment.
? Handout: Statistics Application Evaluation Criteria (Word document)

This handout will guide you in completing and submitting your multiple regression Application 1 Assignment for this week.
? Software: PASW Statistics

use the PASW software to complete this week’s Application 1 Assignment.
? Media:
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o “Why Critique Research” (9:21)