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Multiple regressions and multiple correlations deals with the relationship of one variable compared with a number of other variables It is similar to the bivariate correlation because it describes the degree of linear relationship between two variables Though the multiple correlation assigns one variable to be the criterion or dependent variable and the other variable is the total of the independent variable or predictor The total of the independent variable is found by computing weights so the correlation between the predictor and the criterion is as large as possible The multiple regression is better than the bivariate regression because it examines curvilinear relationships between variables and investigates interactions between continuous independent variablesIn the present experiment the multiple regression and multiple correlation was used to compare different predictors of reading skills It was thought that working memory ability was not as good of a predictor of reading skill as exposure to print The results from this experiment showed that the overall correlation was significant R 59 F 5147 1545 p 0001 meaning adding one adding one variable to the prediction equation significantly increases the degree of multiple correlation It was also shown that the best predictors for reading ability were exposure to print t 142 5501 p 0001 and non-verbal ability measured by the Ravens test t 142 2953 p 01 The standardized regression equation for the significant coefficients was Z reading 385Z ART 224Z Ravens The partial correlation meaning the correlation between two variables after variations from other variables were removed was 419 for exposure to print and 219 for non-verbal ability The standardized regression equation for all the predictors was Z reading 119Z workmem 385Z ART 224Z Ravens 080Z GPA 150Z IQ Using a stepwise regression analysis it was found that the overall regression was significant R 574 F 5147 23623 p 0001 The best predictors for reading ability
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