Questions On The Equation For Regression

1545 WordsDec 14, 20157 Pages
Question 3-Results Question 3. The following equation was deduced from the Heredia, (2015) question 3, and it was based on the equation for regression. These are the results: Ӯ=b+mx or Ӯ=mx+b, Ӯ= dependent variableoverall, a= constant b, b1=predictor 1GRE score on quantitative b value, x1 = GRE score on quantitative. b2=predictor 2GRE score on verbal b value, x2=GRE score on verbal. B3=predictor 3ability to interact easily b value, x3=ability to interact easily. Equation- Ӯ=a+b1(x1) +b2(x2) +b3(x3) Overall college GPA=2.250+0.002 (GRE, quantitative+0.028(ability to interact). Step 1-If the model is significant with a significant value of 0.014, less than 0.05. High F value (3.907), lower significance value (.014). Step 2=Amounted accounted for=R2=.20320.3% of the variance is accounted for by the predictors. There was a moderate effect size. There is a moderate correlation (R=0.451) between the three predictors variables. They are: (GRE on quantitative, GRE scores on verbal, and the ability to interact easily), and the dependent variable is overall college GPA. B values-GRE scores on quantitative has the greatest influence on the overall college GPA (B=.397) followed by the predictor the ability to interact (B=0.145). The predictor GRE on verbal has a negative influence on the overall GPA (B=-0.26). The predictor GRE score on quantitative is the best predictor (significance=.010). The GRE on verbal is significant at .855 and the capability to interact easily is

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