(T/F) Based on the output below, the standard error of estimate does not show a good model fit?  (T/F) ANOVA output shows a good model fit.  SUMMARY OUTPUT                       Regression Statistics         Multiple R 0.804377596         R Square 0.647023317         Adjusted R Square 0.642533948         Standard Error 45.45264766         Observations 638                     ANOVA             df SS MS F Significance F Regression 8 2382006.449 297750.8062 144.1234247 8.3966E-137 Residual 629 1299478.26 2065.943179     Total 637 3681484.709

Please help interpret this SPSS output of a multiple regression analysis result? DV-  To what extent the product safety incident have changed your perceptions of the involved brand(s) IV'S- Trustworthy , Reliability ,  I don’t know how good the company’s products will be before I buy it. , Preventability

ANOVA             df SS MS F Significance F Regression 1 7195512474 7195512474 6.504373807 0.012309437 Residual 98 1.08413E+11 1106257526     Total 99 1.15609E+11       Please explain this...

If a regression model of the form y= B,+B,x,+... + B,x, is fit to 132 observations on each variable and yields an R´value of 0.87, fill in the blanks in the following ANOVA table. Do all calculations to at least three decimal places. Source of Degrees of freedom Sums of Mean F statistic variation squares squares Regression 69 Error Total

Big Time Corporation wanted to determine the relationship between its monthly operating costs and a potential cost driver, machine hours. The output of a regression analysis showed the following information (note: only a portion of the regression analysis results is presented here) SUMMARY OUTPUT Regression Statistics Multiple R 0.998041188 R Square 0.996086212 Adjusted R Square 0.994781616 Standard Error 917.1714273 Observations 5 ANOVA df SS MS F Significance F Regression 1 642276389.7 642276389.7 763.5208906 0.000104039 Residual 3 2523610.281 841203 427 Total 4 644800000 Coefficients Standard Errort Stat P-value Intercept 6679.617454 931.8558049 7.168080532 0.005592948 3714.03639 X Variable 9.796772265 0.354545968 27.63188178 0.000104039 8.66844876 What is variable cost per machine hour (rounded to the nearest cent)? OA. $6,679.62 OB. $917.17 OC. $9.80 OD. $.99 Lower 95% Upper 95.0% 9645.198517 10.92509577

Please interpret clearly and how to do if based on the tables and charts presented below, interpret the results and report your answer with an academic style. How  should interpret assumptions of the technique used.

Chapter 9, Section 2, Exercise 032 Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 355.21 355.21 14.76 0.000 Residual Error 359 8641.13 24.07     Total 360 8996.34                 Give the F-statistic and p-value.Enter the exact answers.The F-statistic is=The p-value is=

Using the previous regression model, is there a statistically significant relationship between GPA and Salary Expectation at the 5% significance level?  Enter the word "relationship" if a relationship exists and "no relationship" if no relationship exists

What is a residual for a multiple regression model and the data that is used to create it? Select one.   Question 3 options:   A statistic that explains the relationship between response and predictor variables   The predicted value of the response variable using the multiple regression model   A statistic that is used to evaluate the significance of the multiple regression model   The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression model