4.7 Consider the simple linear regression model fi t to the weight and blood pressure datain.SymbolicBPSubjectWeightSubjectWeightSystolic BP16513014172153167133151591281801501616813215512817174149212151181831581751461921515019015020195163210140211801562001482214312414912523240170158133242351651691352519216017015026187159b. Construct and interpret a plot of the residuals versus the predicted response.12345or∞ag1236789

Residual explain the error happen in the data set. It is calculated by the difference of actual and…

Answered: 4.7 Consider the simple linear…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The following estimated regression equation is based on 10 observations yhat = 30.12 + .60x1 + .48x2 SST = 680.3, SSR= 601.4, Sb1 = .0813 and Sb2 = .0567 a. Compute MSR and MSE b. Compute F and perform the appropriate F test. Use alpha = .05. c. Perform a t test for the significance of B1. Use alpha = .05. d. Perform a t test for the significance of B2. Use alpha = .05.
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2 for a sample of N=20N=20 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level α=0.05α=0.05. X1X1 X2X2 YY 65.4 65.8 57.3 72.8 70.8 55.1 63.3 59.9 66.9 59.1 60.4 60.4 65.4 66.9 56.2 58.3 61.9 50.4 57.1 57.1 54.2 78.2 62.5 67.5 54.2 55.9 57.1 56.5 55.5 57.8 57.9 56.2 60.8 54.3 54.8 61.8 68.2 70.5 71.8 60 64.1 58.8 66.6 60.5 54.6 66.7 68.5 51.7 45.1 48.6 57.1 58.4 59.9 55.9 58.6 66.3 52.5 56 60.5 67.1 SSreg=SSres=R2=F=P-value =
In exercise 1, the following estimated regression equation based on 10 observations waspresented. y^= 29.1270 + .5906x1 + .4980x2Here SST =6724.125, SSR =6216.375, Sb1 = .0813, and Sb2 = .0567.a. Compute MSR and MSE.b. Compute F and perform the appropriate F test. Use α .05.c. Perform a t test for the significance of B1. Use α .05.d. Perform a t test for the significance of B2. Use α .05.
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2 for a sample of N=10N=10 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.01α=0.01. X1X1 X2X2 YY 58.8 29.9 63.1 64.1 57.3 40.1 51.4 35.3 46.2 77.1 88.5 30 60.6 67.5 16.2 68.3 63.4 62 44.8 6.6 77.6 49 29.3 65.5 55.5 25.8 62.5 57.5 30.2 62 R2=R2= F=F= P-value for overall model = t1=t1= for b1b1, P-value = t2=t2= for b2b2, P-value = What is your conclusion for the overall regression model (also called the omnibus test)? The overall regression model is statistically significant at α=0.01α=0.01. The overall regression model is not statistically significant at α=0.01α=0.01. Which of the regression coefficients are statistically different from zero? neither regression coefficient is…
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2for a sample of N=20N=20 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level α=0.02. X1X1 X2X2 YY 31.4 32.3 25.2 85.4 28.1 53 66.3 42.6 67.4 59 56.1 70.7 52.4 40.4 39.7 86.4 23.7 35 50.9 36.7 34.4 74.4 38 64.9 57.3 47.6 67.4 61.9 33.3 41.3 48.6 49.7 53.6 46.6 47.2 34.5 31.8 38.7 40.9 86 55 74 69.8 27.7 45.9 65.8 48.2 42.4 44.7 55.3 55.1 57.3 27 31.5 60.4 28.1 19.4 65.9 26 13.7 SSreg= SSres= R2= F= P-value = What is your decision for the hypothesis test? Reject the null hypothesis, H0:β1=β2=0 Fail to reject H0H0 What is your final conclusion? The evidence supports the claim that one or more of the regression coefficients is non-zero The evidence supports the claim that all of the regression…
An econometrician suspects that the residuals of her model might be autocorrelated. Explain the steps involved in testing this theory using the Durbin–Watson (DW) test
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2 for a sample of N=11N=11 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.05α=0.05. X1X1 X2X2 YY 52.3 45.6 49.1 55.9 48.7 53.1 46.5 47.4 45.9 52 45.6 59.8 48.9 45.5 52.6 46.2 35.1 71.2 28.8 32.6 33.5 40.7 41 40.3 43.7 40 65.8 47 37.8 52.8 34.2 28 53.5 R2=R2= (Not the adjusted R2R2) FF test statistic = P-value for overall model = test statistic for b1b1 p-value for the two-tailed test = test statistic for b2b2 p-value for the two-tailed test = What is your conclusion for the overall regression model at the 0.05 alpha level (also called the omnibus test)? The overall regression model is statistically significant at α=0.05α=0.05. The overall…
The following estimated regression equation is based on 10 observations y = 30.12 + .60x1 + .48x2 SST = 680.3, SSR= 601.4, Sb1 = .0813 and Sb2 = .0567 a. Compute MSR and MSE b. Compute F and perform the appropriate F test. Use alpha = .05. c. Perform a t test for the significance of B1. Use alpha = .05. d. Perform a t test for the significance of B2. Use alpha = .05.
The following partial JMP regression output for the Fresh detergent data relates to predicting demand for future sales periods in which the price difference will be .10. SE Fit = .165360573, s = .628152. Predicted Demand Lower 95% MeanDemand Upper 95% MeanDemand 31 8.181072245 7.842346262 8.519798229 StdErr IndivDemand Lower 95% IndivDemand Upper 95% MeanDemand 0.649552965 6.850522511 9.511621980 Click here for the Excel Data File (a) Report a point estimate of and a 95 percent confidence interval for the mean demand for Fresh in all sales periods when the price difference is .10. (Round your CI answers to 3 decimal places and other answer to 4 decimal places.) (b) Report a point prediction of and a 95 percent prediction interval for the actual demand for Fresh in an individual sales period when the price difference is .10. (Round your PI answers to 3 decimal places and other answer to 4 decimal places.) (c) StdErr Indiv Demand on…
A sixth-grade teacher believes that there is a relationship between his students’ IQscores (y) and the numbers of hours (x) they spend watching television each week. Thefollowing table shows a random sample of 7 sixth-grade students.y 125 116 97 114 85 107 105x 5 10 30 16 41 28 21 Does the data provide sufficient evidence to indicate that the simple linear regressionmodel is appropriate to describe the relationship between x and y? Perform a model utilitytest at α = 0.05. (Give H0, Ha, rejection region, observed test statistic, P-value, decisionand conclusion.)Find the Pearson sample correlation coefficient between x and y. Then interpretthe result.
Calculate the R2of the following multivariate sample regression functions and interpret theanswers.3.1 Investment-hat = β1-hat + β2-hat*Interest rate + β3-hat*Exchange rateESS = 900RSS = 1003.2 Investment-hat = β1 + β2-hat*Interest rate + β3-hat*number of 311 studentsESS = 400RSS = 6003.3 Salary-hat = β1 + β2-hat*Frequency of blinking eyes + β3-hat*Colour of hairRSS = 950TSS = 1000
A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2for a sample of N=13N=13 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test statistics to assess the significance of the regression model and partial slopes. Use a significance level α=0.02α=0.02. X1X1 X2X2 YY 40.6 66.7 59 27.2 72.4 42.3 65 56.2 69.1 17.3 71.2 25.4 30 65.6 40.9 41.2 59.1 44.8 68.5 44.3 40.6 79.5 37.3 54.7 55.6 58 66.3 59.4 46.1 27.2 62.9 42.4 30.9 67.2 44.5 39.5 22.6 64.3 18.4 R2= F= P-value for overall model = t1= for b1, P-value = t2= for b2, P-value = What is your conclusion for the overall regression model (also called the omnibus test)? The overall regression model is statistically significant at α=0.02. The overall regression model is not statistically significant at α=0.02. Which of the regression coefficients are statistically different from zero? neither…

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