Regression

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7 Terms

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Regression

Predicts the relationship between two or more variables

Quantifies the strength of the relationship between the IV and DV

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Regression assumptions

The rela between IV and DV is linear

Interval or ratio level data

The errors are normally distributed

<p>The rela between IV and DV is linear</p><p>Interval or ratio level data</p><p>The errors are normally distributed</p>
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Types of Regression

Linear: IV predict the linear value of a DV

Bivariate: Two variables

Multivariate: Three or more

Logistic: DV are NOMINAL or ORDINAL

Quadratic: Applies quadratic formula to produce a parabola of best fit

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R

Correlation between two variables

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R Square

The amount of variance in the dependent variable explained by the independent variable

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Regression equation

Y - predicted value of the DV

a = y intercept

b = slope of the regression line

x = value of the IV

<p>Y - predicted value of the DV</p><p>a = y intercept</p><p>b = slope of the regression line</p><p>x = value of the IV</p>
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Standardized Beta

Estimates the predicted power of each IV