Introduction to Sociological Research_Kupchik_Date__042610

Introduction to Sociological Research_Kupchik_Date__042610...

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When using multiple regression, we regress the dependent variable on several independent variables simultaneously. The regression tells us how each independent variable affects the dependent variable while controlling for all other independent variables. A multivariate regression equation is: Y = a + b 1 x 1 + b 2 x 2 + e Each regression coefficient (slope) tells us how much the dependent variable increases (or decreases if negative) per unit increase in the independent variable, while controlling for each other independent variable. This tells us the unique association between each independent variable and the dependent variable. The formula for computing a regression coefficient in a model with 2 independent variables is: b 1 = s y * r yx1 – r yx2 r x1x2 s x1 1-r 2 x1x2 The formula for calculating the y-intercept is: The (unstandardized) regression coefficient tells us the impact of the independent variable on the dependent variable in real units, which is our most important piece of information. Yet since this is determined by the measurement scale of the variables, we need a way to
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This note was uploaded on 08/30/2010 for the course SOCI 301 taught by Professor Kupchick during the Spring '09 term at University of Delaware.

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Introduction to Sociological Research_Kupchik_Date__042610...

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