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##### Saint GBA334 week 3 quiz (in class)

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Question 1. 1.;The variable to be predicted is the dependent variable.;(Points: 4);True;False;Question 2. 2.;If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that;(Points: 4);Y = a + bX is a good forecasting method.;Y = a + bX is not a good forecasting method.;a multiple linear regression model is a good forecasting method for the data.;a multiple linear regression model is not a good forecasting method for the data.;None of the above;Question 3. 3.;A judgmental forecasting technique that uses decision makers, staff personnel, and respondent to determine a forecast is called;(Points: 4);exponential smoothing.;the Delphi method.;jury of executive opinion.;sales force composite.;consumer market survey.;Question 4. 4. Which of the following statements about scatter diagrams is true? (Points: 4);Time is always plotted on the y-axis.;It can depict the relationship among three variables simultaneously.;It is helpful when forecasting with qualitative data.;The variable to be forecasted is placed on the y-axis.;It is not a good tool for understanding time-series data.;Question 5. 5.;Which of the following is not classified as a qualitative forecasting model?;(Points: 4);exponential smoothing;Delphi method;jury of executive opinion;sales force composite;consumer market survey;Question 6. 6.;The correlation coefficient resulting from a particular regression analysis was 0.25. What was the coefficient of determination?;(Points: 4);0.5;-0.5;0.0625;There is insufficient information to answer the question.;None of the above;Question 7. 7.;Which of the following is a technique used to determine forecasting accuracy?;(Points: 4);exponential smoothing;moving average;regression;Delphi method;mean absolute percent error;Question 8. 8.;The condition of an independent variable being correlated to one or more other independent variables is referred to as;(Points: 4);multicollinearity.;statistical significance.;linearity.;nonlinearity.;The significance level for the F-test is not valid.;Question 9. 9.;A prediction equation for starting salaries (in $1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what does the coefficient of determination of 0.87425889 mean?;SUMMARY OUTPUT;Regression Statistics;Multiple R;0.935018125;R-Square;0.87425889;Adjusted R-Square;0.860287655;Standard Error;3.3072944;Observations;11;ANOVA;df;F;Significance F;Regression;1;62.57564;0.000024;Residual;9;Total;10;Coefficients;t-Statistics;p-Value;Intercept;-29.1406;-3.36493;0.008324;SAT;0.06544;7.910476;0.0000242;(Points: 4);A coefficient of determination of 0.87425889 means that there is a strong correlation between starting salaries and SAT scores.;A coefficient of determination of 0.87425889 means that SAT is not a good predictor of starting salaries.;A coefficient of determination of 0.87425889 means that 87.425889 percent changes in starting salaries have been accounted for by changes in SAT scores.;A coefficient of determination is not a good measure of the relationship between starting salaries and SAT scores.;None of the above;Question 10. 10.;The coefficient of determination resulting from a particular regression analysis was 0.85. What was the correlation coefficient, assuming a positive linear relationship?;(Points: 4);0.5;-0.5;0.922;There is insufficient information to answer the question.;None of the above;Question 11. 11. Time-series models attempt to predict the future by using historical data. (Points: 4);True;False;Question 12. 12.;A prediction equation for starting salaries (in $1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what does the significance F meanl?;SUMMARY OUTPUT;Regression Statistics;Multiple R;0.935018125;R-Square;0.87425889;Adjusted R-Square;0.860287655;Standard Error;3.3072944;Observations;11;ANOVA;df;F;Significance F;Regression;1;62.57564;0.000024;Residual;9;Total;10;Coefficients;t-Statistics;p-Value;Intercept;-29.1406;-3.36493;0.008324;SAT;0.06544;7.910476;0.0000242;(Points: 4);The significance F means that starting salary is a good predictor of SAT scores.;The significance F means that SAT score is a good predictor of starting salary.;The significance F means that SAT score is not a good predictor of starting salary.;The significance F means that starting salary is not a good predictor of SAT score.;None of the above.;Question 13. 13.;One purpose of regression is to predict the value of one variable based on the other variable.;(Points: 4);True;False;Question 14. 14. A moving average forecasting method is a causal forecasting method. (Points: 4);True;False;Question 15. 15. The most common quantitative causal model is regression analysis. (Points: 4);True;False;Question 16. 16.;The Delphi method solicits input from customers or potential customers regarding their future purchasing plans.;(Points: 4);True;False;Question 17. 17. Which of the following methods tells whether the forecast tends to be too high or too low? (Points: 4);MAD;MSE;MAPE;decomposition;bias;Question 18. 18. Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day moving average. (Points: 4);14;13;15;28;12.5;Question 19. 19.;In regression, an independent variable is sometimes called a response variable.;(Points: 4);True;False;Question 20. 20.;The correlation coefficient has values between?1 and +1.;(Points: 4);True;False;Question 21. 21.;The coefficient of determination takes on values between -1 and + 1.;(Points: 4);True;False;Question 22. 22.;Enrollment in a particular class for the last four semesters has been 122, 128, 100, and 155 (listed from oldest to most recent). The best forecast of enrollment next semester, based on a three-semester moving average, would be;(Points: 4);116.7.;126.3.;168.3.;135.0.;127.7.;Question 23. 23.;Daily demand for newspapers for the last 10 days has been as follows: 12, 13, 16, 15, 12, 18, 14, 12, 13, 15 (listed from oldest to most recent). Forecast sales for the next day using a two-day weighted moving average where the weights are 3 and 1 are;(Points: 4);14.5.;13.5.;14.;12.25.;12.75.;Question 24. 24.;A prediction equation for starting salaries (in $1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what can be said about the level of significance for the overall model?;SUMMARY OUTPUT;Regression Statistics;Multiple R;0.935018125;R-Square;0.87425889;Adjusted R-Square;0.860287655;Standard Error;3.3072944;Observations;11;ANOVA;df;F;Significance F;Regression;1;62.57564;0.000024;Residual;9;Total;10;Coefficients;t-Statistics;p-Value;Intercept;-29.1406;-3.36493;0.008324;SAT;0.06544;7.910476;0.0000242;(Points: 4);SAT is not a good predictor for starting salary.;The significance level for the intercept indicates the model is not valid.;The significance level for SAT indicates the slope is equal to zero.;The significance level for SAT indicates the slope is not equal to zero.;None of the above;Question 25. 25.;A prediction equation for starting salaries (in $1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what is the regression equation?;SUMMARY OUTPUT;Regression Statistics;Multiple R;0.935018125;R-Square;0.87425889;Adjusted R-Square;0.860287655;Standard Error;3.3072944;Observations;11;ANOVA;df;F;Significance F;Regression;1;62.57564;0.000024;Residual;9;Total;10;Coefficients;t-Statistics;p-Value;Intercept;-29.1406;-3.36493;0.008324;SAT;0.06544;7.910476;0.0000242;(Points: 4);Starting Salaries = 0.06544 - 29.1406SAT;Starting Salaries = -29.1406 + 0.06544SAT;Starting Salaries = 0.935018125 + 0.6544SAT;Starting Salaries = 0.87425889 + 0.06544SAT;None of the above

Paper#20383 | Written in 18-Jul-2015

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