Please help me with my practice quiz for Statics for Managers. Images are attached. Thank you,
Question 7 (1 point) The scatter plot is a two dimensional graph that is used to graphically represent the relationship between two variables. Question 8 (1 point) The correlation coefficient provides information about the curved nature between 2 variables. Question 1 (1 point) For a sample of n = 18, the correlation between amount of ice cream sold and temperature was calculated to be 0.61. What are the appropriate null and alternative hypotheses to test for correlation? HO: p = 0 ; HA: p # 0 HO: p 2 0 ; HA: P 0Question 10 (1 point) If the calculated sample correlation between two variables is r=O.372 and n = 36, what is the test statistic value for testing whether the true population correlation coefficient is equal to zero? Question 11 (1 point) If a sample correlation coefficient is r=.38 and the sample size is 15, which of the following is appropriate critical value for testing the null hypothesis of p = O at an alpha=.05 level? Question 12 (1 point) Regression Statistics Multiple R 0.82731 R Square 0.68445 Adjusted R Square 0.60030 Standard Error 37.40252 Observations 20 ANOVA df SS MS F Significance F Regression 4 45515.77 11378.94 8.13 0.00107 Residual 15 20984.23 1398.95 Total 19 66500.00 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 120.50886 82.22254 1.46564 0.16339 -54.74434 295.76205 Rooms 7.46415 12.24022 0.60981 0.55112 -18.62526 33.55355 Age -1.7783 0.7179 -2.47713 0.02564 -0.33084 -0.02482 Length 2.82719 1.40160 2.01711 0.06195 -0.16025 5.81463 Nav. Equip. 0.35408 0.22411 1.57995 0.13497 -0.12360 0.83176 Given the regression output above, what percent of variation is explained by the model? about 68% about 60% about 83% about 37%Question 13 (1 point) Regression Statistics Multiple R 0.82731 R Square 0.68445 Adjusted R Square 0.60030 Standard Error 37.40252 Observations 20 ANOVA SS MS F Significance F Regression 45515.77 11378.94 8.13 0.00107 Residual 15 20984.23 1398.95 Total 19 66500.00 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 120.50886 82.22254 1.46564 0.16339 -54.74434 295.76205 Rooms 7.46415 12.24022 0.60981 0.55112 -18.62526 33.55355 Age -1.7783 0.7179 -2.47713 0.02564 -0.33084 -0.02482 Length 2.82719 1.40160 2.01711 0.06195 -0.16025 5.81463 Nav. Equip 0.35408 0.22411 1.57995 0.13497 -0.12360 0.83176 Given the regression output above, where the dependent variable is cost of a boat, which independent variables are significant at the alpha = 10% level? Select all that are correct. rooms age nav equipment lengthQuestion 14 (1 point) Regression Statistics Multiple R 0.82731 R Square 0.68445 Adjusted R Square 0.60030 Standard Error 37.40252 Observations 20 ANOVA SS MS F Significance F Regression 4 45515.77 11378.94 8.13 0.00107 Residual 15 20984.23 1398.95 Total 19 66500.00 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 120.50886 82.22254 1.46564 0.16339 -54.74434 295.76205 Rooms 7.46415 12.24022 0.60981 0.55112 -18.62526 33.55355 Age -1.7783 0.7179 -2.47713 0.02564 -0.33084 -0.02482 Length 2.82719 1.40160 2.01711 0.06195 -0.16025 5.81463 Nav. Equip 0.35408 0.22411 1.57995 0.13497 -0.12360 0.83176 Given the regression output above, where the dependent variable is cost of a boat, is the model as a whole significant? How do you know? yes, the intercept is significant. Oyes, the F has a significance <.1 o no not all of the independent variables are significant. oyes r-squared is>.5Question 15 (1 point) 31m ' " "i'lJ'Thu 145354135591 7303579595 41.. 01950.35 453.4% 1442-73} ____. _!_991934319?'!_._2-552111$2. 1 4521mm i 171312249 Given the regression equation above where the dependent variable is the price of a computer, what should the degrees free for the Regression Sum of Squares be? Question 16 (1 point) SUMMARY OUTPUT Regression Statistics Multiple R 0.834308875 R Square Adjusted R Square Standard Error Observations ANOVA SS MS F ignificance F Regression 3 34335282.67 2.07E-08 Residual 14991966.89 Total 35 49327249.56 Coefficients |Standard Error t Stat | P-value Lower 95% Upper 95% Intercept -45.95413592 730.8679496 -0.06288 0.950256 -1534.68 1442.774 Processor Mz 0.193481924 2.557161186 RAM 4.521583654 2.94317936 Hard Drive Capacity 174.042249 44.08895333 Given the regression equation above where the dependent variable is the price of a computer, what is the R-square of the regression? O 0.914 0.166 0.304 0.696Question 17 (1 point) SUMMARY OUTPUT Regression Statistics Multiple R 0.834308875 R Square Adjusted R Square Standard Error Observations ANOVA df SS MS F ignificance F Regression 3 34335282.67 2.07E-08 Residual 14991966.89 Total 35 49327249.56 Coefficients Standard Error | t Stat | P-value Lower 95% Upper 95% Intercept -45.95413592 730.8679496 -0.06288 0.950256 -1534.68 1442.774 Processor Mz 0.193481924 2.557161186 RAM 4.521583654 2.94317936 Hard Drive Capacity 174.042249 44.08895333 Given the regression equation above where the dependent variable is the price of a computer, what is the t-stat for processor Mz? 0.960 1.537 0.0757 O0.193Question 18 (1 point) W " 'i'UU'iPU ' ' I I , 45345.1 \"42.77412 __2.557_ __1__a_11as a.\" Given the regression equation above where the dependent variable is the price of a computer, what is the F-value for the model? Question 19 (1 point) Saved SUMMARY OUTPUT Regression Statistics Multiple R 0.834308875 R Square Adjusted R Square Standard Error Observations ANOVA di SS MS F ignificance F Regression 3 34335282.67 2.07E-08 Residual 14991966.89 Total 35 49327249.56 Coefficients Standard Error | t Stat | P-value Lower 95% Upper 95% Intercept -45.95413592 730.8679496 -0.06288 0.950256 -1534.68 1442.774 Processor Mz 0.193481924 2.557161 186 RAM 4.521583654 2.94317936 Hard Drive Capacity 174.042249 44.08895333 Given the regression equation above where the dependent variable is the price of a computer, which independent variables has the lowest p-value? Processor Mz Hard Drive Capacity O Cannot be determined with table given.Question 2 (1 point] For a sample of n = 18, the correlation between amount of ice cream sold and temperature was calculated to be 0.61. Use 0t=0.10. Calculate the ttest statistic for correlation. Question 3 (1 point) For a sample of n = 18, the correlation between amount of ice cream sold and temperature was calculated to be 0.61. Based on the sample results, we are testing to determine whether there is a significant correlation between these two variables. Determine the critical value for the rejection region for the test statistic t, using 0(=0.10. Question 4 (1 point) For a sample of n = 18, the correlation between amount of ice cream sold and temperature was calculated to be 0.61. Based on the sample results, we are testing to determine whether there is a significant correlation between these two variables. Use 01:0.10. Would you reject the null hypothesis that there is correlation between the 2 variables? 0 Yes, reject the null because the calculated t-statistic is greater than the critical t- value. 0 No, do not reject the null because the calculated t-statistic is less than the critical t-statistic. O No, do not reject the null because the calculated t-statistic is greater than the critical t-value. 0 Yes, reject the null because the calculated t-statistic is less than the critical t- statistic. Question 5 (1 point] We have collected costs for private and state universities. Data is in dollars and was collected for 6 different regions. Use linear regression analysis where the cost for a private university is predicted by the cost of a state university. Calculate the beta and significance for private using 0t=0.05. Ob # Pub Private 1 10,075 2,069 2 10,030 2,304 3 13,096 3,153 4 12,592 3,636 5 15,928 4,611 6 17,116 5,668 0 bl = 5,702, NOT significant at the 5% level 0 bl = 2.08, significant at the 5% level 0 bl = 2.08, NOT significant at the 5% level 0 bl = 5,702, significant at the 5% level Question 6 (1 point) We have collected costs for private and state universities. Data is in dollars and was collected for 6 different regions. Use linear regression analysis where the cost for a private university is predicted by the cost of a state university. Calculate the beta and significance for private using 0(=0.05. Using your model, when the public cost is $8,000, what is the expected cost for a private university? Ob# Pub Private 1 10,075 2,069 2 10,030 2,304 3 13,096 3,153 4 12,592 3,636 5 15,928 4,611 6 17,116 5,668 0 $45,762 Q $22,330 0 $13,720 0 $16,640 Question 9 (1 point) If the correlation between two variables is found to be -O.70, which of the following is true? 0 There is a positive linear relationship between the two variables. 0 There is a fairly strong negative linear relationship between the two variables. 0 The scatter diagram for the two variables will be upward sloping from left to right. 0 An increase in one of the variables will cause the other variable to decline by 70 percent
