Bluman A.G. Elementary Statistics- A Step By Step Approach

582 Chapter 10 Correlation and Regression4. Double-click C1 GPA, then C2 AGE.5. Click on [Storage].a) Check the box for Residuals.b) Check the box for Fits.6. Click [OK] twice.Regression Analysis: SCORE versus GPA, AGEThe regression equation isSCORE = -44.8 + 87.6 GPA + 14.5 AgePredictor Coef SE Coef T PConstant -44.81 69.25 -0.65 0.584GPA 87.64 15.24 5.75 0.029AGE 14.533 2.914 4.99 0.038S = 14.0091 R-Sq = 97.9% R-Sq(adj) = 95.7%Analysis of VarianceSource DF SS MS F PRegression 2 18027.5 9013.7 45.93 0.021Residual Error 2 392.5 196.3Total 4 18420.0The test statistic and P-value are 45.93 and 0.021, respectively. Since the P-value is less thana, reject the null hypothesis. There is enough evidence in the sample to conclude the scores arerelated to age and grade point average.TI-83 Plus orTI-84 PlusStep by StepThe TI-83 Plus and the TI-84 Plus do not have a built-in function for multiple regression.However, the downloadable program named MULREG is available on your CD and OnlineLearning Center. Follow the instructions with your CD for downloading the program.Finding a Multiple Regression Equation1. Enter the sets of data values into L 1 , L 2 , L 3 , etc. Make note of which lists contain theindependent variables and which list contains the dependent variable as well as how manydata values are in each list.2. Press PRGM, move the cursor to the program named MULREG, and press ENTER twice.3. Type the number of independent variables and press ENTER.4. Type the number of cases for each variable and press ENTER.5. Type the name of the list that contains the data values for the first independent variable andpress ENTER. Repeat this for all independent variables and the dependent variable.10–50