Answer: 62. 77 thousand
QUESTION 6 ANOVA df Regression 0.72 Residual 10 62.6 63.32 Total Std Error Coefficients 14.64 Intercept 146.76 1.99 No....
QUESTION 6 ANOVA df Regression 0.72 Residual 10 62.6 63.32 Total Std Error Coefficients 14.64 Intercept 146.76 1.99 No. of accounts (000) 5.87 This printout is for data relating the number of ATM withdrawals (in thousands) to the number of accounts (in thousands) at that branch. Predict the number of withdrawals if the number of accounts is 24.19 thousand. State the answer in thousands correct to two decimal places. QUESTION 6 ANOVA df Regression 0.72 Residual 10 62.6 63.32 Total...
ANOVA df SS Regression 1 0.72 Residual 10 62.6 Total 11 63.32 Coefficients Std Error Intercept 14.64 146.76 No. of accounts (000) 1.99 5.87 This printout is for data relating the number of ATM withdrawals (in thousands) to the number of accounts (in thousands) at that branch. Predict the number of withdrawals if the number of accounts is 24.528 thousand. State the answer in thousands correct to two decimal places.
ANOVA df SS Regression 1 882 Residual 20 4000 Total 21 4882 Coefficients Standard Error t Stat Intercept 5.00 3.56 Variable x 6.30 3.00 Use the ANOVA table that was provided in question 7 and Perform an F test and determine whether x and y are related. Use α = .05 Answer Options: Since the test statistic F = 3.45 < 4.35 ,Fail to reject HO Since the test statistic F = .45< 3.45, Fail to reject HO Since the...
ANOVA DF SS MS Regression 1 0.0994 0.0985 Residual 62 0.1413 0.0025 Total 61 0.2407 Coefficients Standard Error Intercept -0.013 0.0053 S&P 500 Returns 1,2139 0.1878 Looking both at the specification of the model and at the estimated coefficient, how can you interpret the coefficient of S&P 500 Returns
A regression model relating x, number of salespersons at a branch office, to y, annual sales at the office (in thousands of dollars) provided the following computer output from a regression analysis of the data. Where n total=26. a. Write the estimated regression equation (to whole number). y=_____+_____x b. Compute the F statistic and test the significance of the relationship at a .05 level of significance. (to 2 decimals) F-value ____ p-value is _______, we _________ h0 c. Compute the...
J. Thie uala set is 1or b4 banks. R2 Std. Error 6.977 0.519 64 ANOVA table Source df MS F p-value 1 3,260.0981 66.97 1.90E-11 62 3,260.0981 3,018.3339 Regression Residual 48.6828 Total 6,278.4320 63 Regression output Confidence Interval Lower 95% Upper 95% variables Coefficients Std. Error tStt p-value Intercept 65763 1.9254 3.416 0011 2.727510.4252 X1 00452 0.0055 8.183 1.90E-11 0.0342 0.0563 Calculate the R2 a. b. In words what does the R? say about total revenue for a bank? c....
A regression model relating 3, number of salespersons at a branch office, to y, annual sales at the office in thousands of dollars) provided the following computer output from a regression analysis of the data. Where ntotal = 32. ANOVA df MSF Significance F SS 6863.5 Regression Residual Total 9342.6 Stat P-value Intercept Number of Salespersons Coefficients 88.0 54.0 Standard Errort 12.175 5.865 a. Write the estimated regression equation (to whole number). y= Xx b. Compute the F statistic and...
only part II is needed Regardless of your answer to (a), you come up with the following multiple regression model. b. Coefficients: Estimate Std. Error t value Pr>lt (Intercept) 72.2285 1.2697 56.89 2e-16 X2 X3 Residual standard error: 7.25 on 191 degrees of freedom Multiple R-squared: 0.494, Adjusted R-squared: 0.489 F-statistic: 93.3 on 2 and 191 DF, p-value: <2e-16 0.4590 0.0524-8.76 1.1e-15 0.4146 0.1290 3.21 0.0015** I) What percentage of the total variation in Life Expectancy can you explain with...