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Psyc_315_-_Winter_2010_-_Class_9 - Recap of Last Class...

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1 Recap of Last Class Steps to Calculating Pearson r Correlation and Causation Factors Influencing Pearson r • Prediction • Questions? Chapter 8 Correlation and Prediction 3 Recap: Correlation vs. Prediction When a bivariate trend is reasonably linear, a line of “best fit” can be found and used to predict values of Y from X. Such a line is called a regression line , and the prediction is made by noting the Y value of the point on the line that corresponds to the particular value of X. For r = ±1.00, each predicted Y value would fall exactly on the regression line, and prediction would be errorless. With any lesser correlation, there will be some prediction error . The lower the correlation, the greater the prediction error.
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4 Recap: Correlations and Predictions Correlations can be used to make predictions about scores. Predictor: – X variable – Variable being predicted from (e.g., SAT scores). – Independent variable Criterion: – Y variable. – Variable being predicted (e.g., First year GPA). – Dependent variable 5 The Regression Equation Every straight line has an equation; the regression line is no exception. The location of the regression line in a scatterplot is determined by the regression equation . A straight line is defined by the slope and the intercept .
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