Table 8.1: Selected Excel output from a simple linear regression of levels of stress and average hours of cycling a week; n=80 ANOVA Significance F df S MS Regression 1 330.0887 330.0887 439.5926 8.61E-34 Residual 78 58.56994 0.750897 Total 79 388.6586 Standard Coefficients Error t Stat P-value Intercept Hours of cycling 8.174779154 0.201398 40.59015 <0.0001 (week) -0.151563181 0.007229 -20.9665 <0.0001 By looking at the output in Table 8.1, write down the equation of the fitted regression model, and explain the meaning of the regression coefficients in context. Comment on the statistical significance of the regression coefficients.

A multiple regression analysis produced the following tables. Predictor Coefficients StandardErrort Statistic p-valueIntercept -139.609 2548.989 -0.05477 0.957154x 24.24619 22.25267 1.089586 0.295682x 32.10171 17.44559 1.840105 0.08869Source df SS MS F p-valueRegression 2 302689 151344.5 1.705942 0.219838Residual 13 1153309 88716.07Total 15 1455998Using = 0.01 to test the null hypothesis H :?1 = ?2 = 0, the critical F value is ____.6.701.964.845.995.70

Which of the following tools is not appropriate for studying the relationship between two numerica variables? Correlation coefficient Scatter plot Historam Regression

A student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings(x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained.   ANOVA                                   df                  SS Regression                3                   45.9634 Residual                  11                   2.6218 Total                                 Coefficients     Standard Error Intercept                0.0136 x1                          0.7992                   0.074 x2                          0.2280                   0.190 x3                         -0.5796                   0.920   Write out the estimated regression equation for the relationship between the variables.  Compute coefficient of determination. What can you say about the strength of this relationship?  Carry out a test to determine whether y is…

Do the following plots show 1. Constant variability  2. Nearly normal residuals 3.  Independent observations for SLR (conditions for linear regression)

Following is a portion of the regression output for an application relating maintenance expense (dollars per month) to usage (hours per week) for a particular brand of computer terminal. Excel File: data14-41.xlsx ANOVA df SS MS F Significance F Regression 1575.76 Residual 8 349.14 Total 1924.90 Coefficients Standard Error t Stat P-value Intercept 6.1092 0.9361 Usage 0.8951 0.149 If your answer is zero, enter "0". a. Write the estimated regression equation (to 4 decimals). ŷ = b. Use a t test to determine whether monthly maintenance expense is related to usage at the 0.05 level of significance (to 2 decimals). Use Table 2 of Appendix В. t = p-value - Select your answer v the null hypothesis. Monthly maintenance expense Select your answer - related to usage. c. Did the estimated regression equation provide a good fit? Explain. Hint: If r is greater than 0.50, the estimated regression equation provides a good fit. - Select your answer - V because the value of r2 is - Select your answer -…