Data on Advertising Expenditures and Revenue (each measured in thousands of dollars) was collected and Excel was used to run a Regression Analysis on the data. The Excel-generated output is provided below: ANOVA   df SS MS F Signficance F Regression 1 571.4127907 571.4127907 38.03889695 0.003508906 Residual 4 60.0872093 15.02180233     Total 5 631.5           Coefficients Standard Error  t Stat  P-value  Intercept 32.76744186 2.865238148 11.43620187 0.000333583 Expend 1.578488372 0.255933673

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 answer please : 1: Carry out a test to see if x3 and y are significantly related. Use a 5% level of significance.

Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.9086 A 0.8181 398.0910 Observations ANOVA df SS MS Significance F Regression 2 1.50876E-18 Residual C 7448393.148 F Total 49 42699148.82 Coefficients Standard Error t Stat P-value Intercept 1304.9048 197.6548 6.6019 3.28664E-08 Income ($1000s) 33.1330 3.9679 H 7.68206E-11 Household Size 356.2959 33.2009 10.7315 3.12342E-14 a. Complete the missing entries from A to H in this output b. Estimate the annual credit card charges for a three-person household with an annual income of $40,000. C. Did the estimated regression equation provide a good fit to the data? Explain

The owner of a new pizzeria in town wants to study the relationship between weekly revenue and advertising expenditures. All measures are recorded in thousands of dollars. The summary output for the regression model is given below.ANOVA   dfdf SSSS MSMS F� Significance F� Regression 33 18.154037618.1540376 6.051345876.05134587 17.6080562317.60805623 4.3383E-034.3383E-03 Residual 55 1.7183457921.718345792 0.343669160.34366916     Total 88 19.8723833919.87238339         Step 2 of 3 :   What is the adjusted coefficient of determination for this model, R2a��2? Round your answer to four decimal places

Dex Research Limited conducted a research to investigate consumer characteristics that can be used to predict the amount charged by credit card users. The following multiple regression output is based on a data collected by this research company on annual income, household size and annual credit card charges for a sample if 50 consumers. Regression Statistics         Multiple R 0.9086         R Square A         Adjusted R Square 0.8181         Standard Error 398.091         Observations B                     ANOVA             df SS MS F Significance F Regression 2 C E G 1.50876E-18 Residual D 7448393 F     Total 49 42699149                                 Coefficients Standard Error t Stat P-Value   Intercept 1304.9048 197.6548 6.6019 3.28664E-08   Income ($1000s) 33.1330 3.9679 H 7.68206E-11   Household size 356.2959 33.2009 10.7315 3.12342E-14   a. Complete the missing entries from A to H in this outputb. Estimate the annual credit card charges…

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

Data on Advertising Expenditures and Revenue (each measured in thousands of dollars) was collected and Excel was used to run a Regression Analysis on the data. The Excel-generated output is provided below: ANOVA             df SS MS F Significance F Regression 1 571.4127907 571.4127907 38.03889695 0.003508906 Residual 4 60.0872093 15.02180233     Total 5 631.5                     Coefficients Standard Error t Stat P-value   Intercept 32.76744186 2.865238148 11.43620187 0.000333583   Expend 1.578488372 0.255933673 6.167568155 0.003508906   Suppose that you will run the T-test on . a. State the value of , the T Test Statistic (TS) that you would use to run this test. Round off your answer to the fourth decimal place.  =  Blank 1. Fill in the blank, read surrounding text. b. State the value of the PValue (PV) for the Test Statistic in part (a) above. Round off your answer to the fourth decimal place. The PV =  Blank 2. Fill in the blank, read surrounding text.

The owner of a new pizzeria in town wants to study the relationship between weekly revenue and advertising expenditures. All measures are recorded in thousands of dollars. The summary output for the regression model is given below.ANOVA   dfdf SSSS MSMS F� Significance F� Regression 11 20.2147598620.21475986 20.2147598620.21475986 20.9811354520.98113545 0.0013268390.001326839 Residual 99 8.6712580048.671258004 0.963473110.96347311     Total 1010 28.8860178628.88601786         Step 1 of 3:  What is the coefficient of determination for this model, R2�2? Round your answer to four decimal places.

The owner of a new pizzeria in town wants to study the relationship between weekly revenue and advertising expenditures. All measures are recorded in thousands of dollars. The summary output for the regression model is given below.ANOVA   dfdf SSSS MSMS F� Significance F� Regression 11 20.2147598620.21475986 20.2147598620.21475986 20.9811354520.98113545 0.0013268390.001326839 Residual 99 8.6712580048.671258004 0.963473110.96347311     Total 1010 28.8860178628.88601786         Step 3 of 3:  Which statistic is most appropriate for the pizzeria owner to determine the usefulness of the regression model and why?

In the following regression, X = total assets ($ billions), Y = total revenue ($ billions), and n = 64 large banks.      R2 0.519 Std. Error 6.977 n 64     ANOVA table Source SS df MS F p-value Regression   3,260.0981     1     3,260.0981     66.97     1.90E-11   Residual   3,018.3339     62     48.6828               Total   6,278.4320     63                         Regression output confidence interval variables coefficients std. error t Stat p-value Lower 95% Upper 95% Intercept   6.5763     1.9254     3.416     .0011     2.7275     10.4252   X1   0.0452     0.0055     8.183     1.90E-11     0.0342     0.0563      (a) Write the fitted regression equation.  yˆy^ =   Not attempted +    Not attempted X (b-1) State the degrees of freedom for a two-tailed test for zero slope, and use Appendix D to find the critical value at α = .05. (Round t critical value to 3 decimal places.)   Degrees of freedom Not attempted tcrit ± Not attempted…