Refer to the sleep deprivation experimentdescribed in Exercises 12.11 and 12.12 and data

Chapter 12, Problem 26

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Refer to the sleep deprivation experimentdescribed in Exercises 12.11 and 12.12 and data setEX1211. The data and the MINITAB and MS Excelprintout are reproduced here.Number of Errors, y 8, 6 6, 10 8, 14Number of Hours without Sleep, x 8 12 16Number of Errors, y 14, 12 16, 12Number of Hours without Sleep, x 20 24MINITAB output for Exercise 12.26MS Excel output for Exercise 12.26Regression Analysis: y versus xThe regression equation isy = 3.00 + 0.475 xPredictor Coef SE Coef T PConstant 3.000 2.127 1.41 0.196x 0.4750 0.1253 3.79 0.005S = 2.24165 R-Sq = 64.2% R-Sq(adj) = 59.8%Analysis of VarianceSource DF SS MS F PRegression 1 72.200 72.200 14.37 0.005Residual Error 8 40.200 5.025Total 9 112.400 MS Excel output for Exercise 12.26 ANOVAdf SS MS F Significance FRegression 1 72.2 72.2 14.368 0.005Residual 8 40.2 5.025Total 9 112.4Coefficients Standard t P- Lower UpperError Stat value 95% 95%Intercept 3 2.1266 1.4107 0.1960 -1.9040 7.9040x 0.475 0.1253 3.7905 0.0053 0.1860 0.7640a. Do the data present sufficient evidence to indicatethat the number of errors is linearly related to thenumber of hours without sleep? Identify the twotest statistics in the printout that can be used toanswer this question.b. Would you expect the relationship between y and xto be linear if x varied over a wider range (say,x 4 to x 48)?c. How do you describe the strength of the relationshipbetween y and x?d. What is the best estimate of the common populationvariance s2?e. Find a 95% confidence interval for the slope of theline