Question

1. Consider the following data set and the Minitab output. Derive (ie., calculate) each number that has a superscript next to it in the upper right-hand comer.. Show all of your work in complete detail. Data Display x Y Row 1 3 14 5 16 7 20 4 2 3 5 13 8 19 23 24 5 6 9 7 10 14 22 9 20 38 10 22 39 Descriptive Statistics: X, Y Variable N NMean SE Mean StDev Minimum Median Q3 Maximum 22.00 39.00 6.43 5.00 10 010.30 2.03 3.00 8.50 15.50 10 022.80 2.86 9.05 13.00 15.50 21.00 27.50 Y Regression Analysis: Y versus X The regression equation is Y8.860 1.353 X Coefficients Соef Term SE Coef T-Value P-Value 0.001 0.000 Constant 8.86 1.64 5.39 0.137 1,353 9.87 X S 2.64641 R-Sq 92.48 R-Sq (adj) 91.5 Analysis of Variance Source DF SS MS P 681.572 681.572 56.028 737.600 97.32 0.000 Regression 8 Error 7.003 9 Total Prediction forY Regression Equation Y8.861.353 x Variable Setting X 14 Fit SE Fit 95% CI 958 PI (21.3009, 34.3142 27.8076 0.978783 (25.5505, 30.0647") Correlation: X, Y Pearson correlation of x and Y0.961

Answer 1

Hene, the regression equation is r- 8.860 + 1.353x coetticeint of constant wale = 8.850 This indicate average change in y variable when no change in x variable It is known as intercept of regression line The p-value corresponding is o.o1 we conclude the slope value is not zero. coethicient of regression - 1. 353 This in dicate the querage change in y variable when unit change in x variable. The p-value corresponding to x = 0.000 The p-value coios we conclue the x variable contribute in y variable 2- squamed valuer R. sq = 92.41 The It indicate the ati variability in the dependent variability by the regression line In the ANOVA table The p-value corresponding to regression IS 0.0oo0 Lo-ogr conclude theeart X uanable contribute to predict regression line The correlation coetticient = 0.gol indicates a strong correlation between independent variable and dependentvariable