Sales (Y) Calls (X1) Time (X2) Years (X3) 51 167 14.9 5 34 133 17.9 4 49 161 19 3 45 185 15.7 1 47 176 16.6 2 47 183 15.1 2 38 122 22.8 3 44 171 16 3 47 157 16.9 1 37 148 18.5 3 51 177 13.5 4 40 144 20.5 0 48 136 15.7 2 52 197 16.5 2 46 145 19.8 0 42 167 20.9 3 37 120 14.2 2 42 148 19.9 1 43 131 21.8 1 49 184 19.7 2 44 150 21.7 1 43 148 18.8 1 55 189 14.2 1 37 152 23.4 0 44 148 15.9 3 43 169 15.7 4 49 188 24.1 1 45 164 19.7 3 45 146 14.2 3 43 173 23.4 2 47 164 18.1 0 48 177 16.4 3 49 160 16 3 51 190 13.3 1 42 135 19 0 37 137 21.4 1 51 167 19.1 1 44 169 10.5 0 46 149 21 3 42 153 18.3 2 45 140 13 3 37 133 23.4 2 52 173 21.9 0 39 156 15.7 4 45 130 24.3 3 37 130 18.4 1 40 125 14.4 4 44 182 18.3 4 Type ONLINE GROUP NONE ONLINE ONLINE ONLINE GROUP GROUP GROUP GROUP NONE NONE ONLINE ONLINE ONLINE ONLINE NONE NONE NONE ONLINE NONE ONLINE ONLINE GROUP ONLINE NONE ONLINE NONE GROUP ONLINE ONLINE ONLINE GROUP ONLINE NONE ONLINE ONLINE ONLINE NONE ONLINE GROUP ONLINE ONLINE NONE GROUP ONLINE NONE NONE IMPORANT NOTE: The Final Exam The following is a SUMMARY of th See Course home > Course project 5 variables SALES represents the number s CALLS represents the number of sa TIME represents the average time p YEARS represents years of expe TYPE represents the type of tra Week2/PartA paper - Descriptive Analyze/interpret 3 individual vari Report your findings for 3 pairs of 1 pair must include a qualitativ Week6/PartB paper - Confidence 4 speculations (use alpha = .10) a. Mean sales per week exceeds b. Proportion receiving online tra c. Mean calls made among those d. Mean time per call is greater t Report your conclusions on each o AND the p-value to explain your fi Compute then explain/interpret co Week7/PartC paper - Regression Calculate then explain/interpret the fo and the independent variables (labe 1. Generate a scatterplot for Y vs X1, 2. Determine the equation of the "bes 3. Determine the coefficient of correla 4. Determine the coefficient of determ 5. Test the utility of this regression m 6. Based on items 1-5, analyze the ab 7. Compute a 95% CI for 1 (the popu 8. Estimate the average for the depen 9. Predict the value of the dependent 10. What can be said about the value range of the sample values? Ex Build a model to predict the depende 11. Prepare a multiple regression mod Explain the equation for this mu 12. Perform the Global Test for Utility 13. Perform the t-test on each indepe recommendation on which indep 48 42 53 37 46 43 45 42 48 39 46 46 45 44 49 41 48 46 48 47 54 45 58 42 50 49 51 57 59 53 49 46 48 45 58 52 48 43 55 44 59 46 41 42 46 45 43 41 49 165 154 178 142 153 166 138 167 171 149 151 162 158 188 149 157 156 172 174 188 180 173 174 138 145 149 152 167 164 165 129 148 135 140 172 183 138 135 174 128 187 145 118 150 138 167 143 143 152 23.4 17.5 15.6 21.8 16.6 20.8 22.3 21.2 15.3 22.2 18.9 19.1 16.4 15.2 24.9 13.6 17.8 14.8 21.9 19.2 13.9 20.8 17.9 19.1 22.3 21.4 14.3 17.1 12.7 16.2 17.9 22.8 21.9 12.7 12.4 15.9 17.1 20.2 18.4 20.9 13.9 16 18.3 12.5 15.5 16.8 17.9 17.3 26.3 5 2 2 1 1 3 2 2 2 1 1 2 1 3 2 3 4 1 2 1 4 2 1 2 3 3 2 2 3 2 3 3 3 2 2 3 5 3 3 4 2 4 2 3 1 2 3 1 0 ONLINE ONLINE ONLINE NONE ONLINE ONLINE NONE NONE ONLINE GROUP GROUP ONLINE ONLINE GROUP ONLINE ONLINE ONLINE ONLINE GROUP ONLINE ONLINE ONLINE ONLINE GROUP GROUP ONLINE GROUP ONLINE GROUP ONLINE GROUP ONLINE GROUP GROUP ONLINE ONLINE ONLINE GROUP ONLINE GROUP ONLINE GROUP GROUP GROUP GROUP GROUP GROUP GROUP ONLINE If any independent variables are the significant independent varia 14. Is this multiple regression model b The has been a SUMMARY of the See Course home > Course project IMPORANT NOTE: The Final Exam 44 49 37 169 166 145 16 19.1 21.2 1 0 3 ONLINE ONLINE NONE PORANT NOTE: The Final Exam closes on SATURDAY of Week8 e following is a SUMMARY of the requirements for each project See Course home > Course project for detailed requirements that apply to each paper SALES represents the number sales made this week. CALLS represents the number of sales calls made this week. TIME represents the average time per call this week. YEARS represents years of experience in the call center. TYPE represents the type of training the employee received. eek2/PartA paper - Descriptive statistics and graphs Analyze/interpret 3 individual variables using graphical and numerical analysis Report your findings for 3 pairs of variables using graphical and numerical analysis 1 pair must include a qualitative variable and 1 pair must NOT include a qualitative variable eek6/PartB paper - Confidence intervals and hypothesis testing 4 speculations (use alpha = .10) a. Mean sales per week exceeds 41.5 per salesperson b. Proportion receiving online training is less than 55% c. Mean calls made among those with no training is less than 145 d. Mean time per call is greater than 15 minutes Report your conclusions on each of the 4 speculations. Use the seven elements of a hypothesis test AND the p-value to explain your findings in simple terms Compute then explain/interpret confidence intervals for each of the 4 variables listed above eek7/PartC paper - Regression analysis lculate then explain/interpret the following 14 tasks/tests using the dependent variable (labeled Y) and the independent variables (labeled X1, X2, and X3) Generate a scatterplot for Y vs X1, including the graph of the "best fit" line. Interpret. Determine the equation of the "best fit" line Determine the coefficient of correlation. Interpret. Determine the coefficient of determination. Interpret. Test the utility of this regression model. Interpret results, including the p-value. Based on items 1-5, analyze the ability of X1 to predict Y Compute a 95% CI for 1 (the population slope). Interpret this interval. Estimate the average for the dependent variable when X1 = 170 using an interval. Interpret. Predict the value of the dependent variable when X1=170 using an interval. Interpret. . What can be said about the value of the dependent variable for values of X1 outside the range of the sample values? Explain. ild a model to predict the dependent variable/Y using all of the independent variables/ X1, X2, and X3 . Prepare a multiple regression model using the designated dependent and 3 independent variables. Explain the equation for this multiple regression model in simple terms. . Perform the Global Test for Utility (F-Test). Explain the conclusion. . Perform the t-test on each independent variable. Explain the conclusions including your recommendation on which independent variables should be kept and which should be discarded. If any independent variables are to be discarded, re-run the multiple regression, including only the significant independent variables, and summarize your finding on this final model. . Is this multiple regression model better than the linear model generated in parts 1-10? Explain. e has been a SUMMARY of the requirements for each project See Course home > Course project for detailed requirements that apply to each paper PORANT NOTE: The Final Exam closes on SATURDAY of Week8 Sales (Y) Years (X3) 34 4 37 0 37 1 37 1 37 1 37 2 37 2 37 3 37 3 38 3 39 1 39 4 40 0 40 4 41 1 41 2 41 3 42 0 42 1 42 2 42 2 42 2 42 2 42 3 42 3 43 1 43 1 43 2 43 3 43 3 43 3 43 4 44 0 44 1 44 1 44 3 44 3 44 3 44 4 44 4 45 1 45 1 45 2 45 2 45 2 45 2 45 3 45 3 45 3 45 3 46 0 46 1 46 1 46 1 46 1 Type GROUP GROUP ONLINE ONLINE NONE NONE ONLINE GROUP NONE GROUP GROUP NONE NONE NONE GROUP GROUP ONLINE NONE NONE ONLINE ONLINE NONE GROUP ONLINE GROUP NONE ONLINE ONLINE ONLINE GROUP GROUP NONE ONLINE NONE ONLINE GROUP ONLINE GROUP NONE GROUP ONLINE ONLINE NONE ONLINE GROUP GROUP NONE GROUP GROUP GROUP ONLINE ONLINE GROUP ONLINE GROUP Sales Years Types 34-59 0-5 (Online, Group, None) 46 46 46 46 47 47 47 47 47 48 48 48 48 48 48 48 48 49 49 49 49 49 49 49 49 49 50 51 51 51 51 51 52 52 52 53 53 54 55 55 57 58 58 59 59 2 3 3 4 0 1 1 2 2 2 2 2 3 3 4 5 5 0 0 1 2 2 3 3 3 3 3 1 1 2 4 5 0 2 3 2 2 4 1 3 2 1 2 2 3 ONLINE NONE ONLINE GROUP ONLINE GROUP ONLINE ONLINE ONLINE ONLINE ONLINE GROUP ONLINE GROUP ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE NONE GROUP ONLINE GROUP GROUP ONLINE ONLINE GROUP NONE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE ONLINE GROUP Quantitative Quantitative Qualatative Week7/PartC paper - Regression analysis Calculate then explain/interpret the following 14 tasks/tests using the dependent variable (labeled Y) and the independent variables (labeled X1, X2, and X3) 1. Generate a scatterplot for Y vs X1, including the graph of the "best fit" line. Interpret. Y is SALES, X is Calls Sales is the number of sales made during the week. Calls is the number of sales calls made during the week. 2. Determine the equation of the "best fit" line y=0.161x + 20.569 Sales= 20.569 + .161 Calls 3. Determine the coefficient of correlation. Interpret. .562973 There is a 56.30% positive relationship between sales made and calls made during the week. This relationship is moderate. 4. Determine the coefficient of determination. Interpret. .316938 31.69% of sales made can be determined by the number of calls made during that week. 5. Test the utility of this regression model. Interpret results, including the p-value. Ho: B1 = 0 Ha: B1 0 p value is 1.08234E-09; or 0.0 This is less than alpha (4.3935), thus we will reject the null hypothesis. There is sufficient evidence. As calls increase, so do sales, resulting in greater earnings and profits. 6. Based on items 1-5, analyze the ability of X1 to predict Y Based on the items above, we know that this is a valid model. We can predict that as calls increase, so will sales. This is a valid model and we can also see this positive relationship in the scatterplot and the line. With that said, it is a good idea to use number of calls to predict the direction of sales. 7. Compute a 95% CI for 1 (the population slope). Interpret this interval. The 95% confidence interval here is 8. Estimate the average for the dependent variable when X1 = 170 using an interval. Interpret. 9. Predict the value of the dependent variable when X1=170 using an interval. Interpret. 10. What can be said about the value of the dependent variable for values of X1 outside the range of the sample values? Explain. Build a model to predict the dependent variable/Y using all of the independent variables/ X1, X2, and X3 11. Prepare a multiple regression model using the designated dependent and 3 independent variables. Explain the equation for this multiple regression model in simple terms. 12. Perform the Global Test for Utility (F-Test). Explain the conclusion. 13. Perform the t-test on each independent variable. Explain the conclusions including your recommendation on which independent variables should be kept and which should be discarded. If any independent variables are to be discarded, re-run the multiple regression, including only the significant independent variables, and summarize your finding on this final model. 14. Is this multiple regression model better than the linear model generated in parts 1-10? Explain