Final Prob 3.) A sales force manager is interested in the effects of training on a group of sales people. She is convinced to a successful career in sales. Yet, she also concedes that other factors may be responsible for greater success in sale education (college or no college). She has compiled some data on 36 sales people that might be able to answer a num data includes: 1) scores related to understanding the company's complicated sales process before and after training, 2 the sales person, and 3) annual sales for the sales person before and after the training. Her trusty assistant, Liliana, sug useful to see if there is a relationship between the change in a score after training and the corresponding change in ye data will have to be manipulated slightly; for example, for observation 12, the change in score was +26 (87-61) and the +29,133 (268,099-238,986). This suggests that new columns of data will be needed in the table of data. Liliana believe regression is appropriate. 1a) Develop a regression model that explains the relationship between Scores and Sales, before and after training. Plac Minitab) below. Also, determine the following the regression formula. 1b ) What is the the R2 1c) Do you believe the regression to be effective in relating the movement of Sales due to the movement in Scores on u process. Offer a reason why or why not. Ans. 1a) Ans. 1b) Ans. 1c) Ans. 1a) Place analysis here Diff. in Score After and Before Training Residual Plot 1.5 1 Residuals 0.5 0 0.8 1 1.2 1.4 1.6 1.8 Diff. in Score After and Before Training 2 people. She is convinced that training is the key for greater success in sales, for example, be able to answer a number of questions. The efore and after training, 2) the education level of rusty assistant, Liliana, suggests that it might be rresponding change in yearly sales. Thus, the e was +26 (87-61) and the change in sales was ble of data. Liliana believes that a simple linear ore and after training. Place the analysis (Excel or e movement in Scores on understanding the sales obs Scores before Scores after (Salesperson) Training Training College Ed.? 83 85 N 166,489 73 94 Y 237,781 86 77 N 75,995 90 64 90 N Y 92,090 64 248,643 69 89 Y 230,373 71 73 N 134,215 95 84 Y 228,740 83 80 N 29,338 93 85 N 107,257 74 76 Y 305,045 61 87 Y 238,986 88 92 N 198,608 87 67 N 158,325 72 71 N 106,689 82 73 N 141,644 79 98 Y 283,687 83 93 Y 199,340 74 75 Y 201,542 89 74 N 260,166 76 83 Y 390,408 63 89 Y 223,731 86 78 N 150,117 79 72 N 95,520 83 85 Y 229,526 76 76 Y 143,256 91 91 N 227,492 74 79 N 125,196 73 65 N 48,124 80 87 Y 210,793 86 81 Y 140,605 77 84 Y 171,861 70 79 N 153,884 92 81 N 161,336 80 68 N 138,517 65 93 Y 227,409 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 Sales Before Training dual Plot 2 Sales after Training 150,258 194,942 120,322 94,612 229,640 196,962 190,025 211,721 84,353 96,278 340,367 268,099 229,955 134,040 88,367 132,143 344,950 288,641 207,100 244,982 455,719 234,215 140,085 72,631 218,874 195,902 240,990 138,925 63,806 198,237 108,678 264,007 200,268 173,929 114,375 304,206 26 29,113 Final Prob4.) You are developing 4 websites for a firm that advertises to individuals that tend to the Right and Left of the political spectrum. You have interviewed 29 individuals to assess their preferences for 4 websites, as either good or bad. You wonder if there is an association between being either Right or Left leaning (politically) and assessing a site as bad. Develop a contingency table that organizes the Right/Left and bads in the various sites. So, count the joint occurrence of Right/bad and Left/bad for the various sites. (See the table below.) 1) Create the contingency table to test for independence of the Right/Left variable and the bads assessed at sites. (Hint: the grand-total of bads should equal 65 and the mechanics of the tables were done in the novice/practice problems) 2) Perform the chi-square test. Is there independence between Political Leaning (Right and Left) and bads for the various sites? Use an alpha of 0.05 Ans. 1) Right/Left Right left Site 1 0 Right/Left Right left Site 1 Contingency Table for "bads" Site 2 Site 3 Site 4 0 0 Expected Values Site 2 Site 3 0 0 0 0 Site 4 <==will need formulas here Ans. 2) duals that tend to als to assess their sociation between lop a contingency joint occurrence of able and the bads anics of the tables ng (Right and Left) ill need formulas here Quality Opinion Right/Left Site 1 Site 2 Site 3 L good good good L good good bad R good good good L good good bad R bad good bad R bad good bad R good bad bad L bad bad bad R good good bad L bad good good L good good bad R bad good bad R good bad good L good bad good L bad bad bad R bad bad bad R bad good bad L good good good L good bad good L good good good L good bad good L good good good R good bad good R good bad bad L good bad bad L bad bad bad R bad bad good R bad bad bad R good good good "bads"= 11 14 16 Site 4 bad bad bad bad good bad bad bad bad bad bad bad bad good bad bad bad bad bad bad good bad good bad good bad bad bad bad 24 total 65 Final Prob5.) After a successful career as a data analyst, you decide it is time to "give-back." A friend that runs a not-for profit educational program for at-risk teens asks you to examine some data and assess the viability of a particular course Fundamentals of Math. Mastering the concepts taught in this course is deemed an essential life skill. Student data rela two resources that are made available to the teens is collected--1) use of Online help sessions, and 2) E-books viewed b teens. You also have data on the number of classes attended by each student. Data on 40 students is shown in the tabl includes their final grade in the course. 1) Create a regression model that forecasts Final Grade using the resources and attendance. Place the results below. Us either Excel of Minitab (I recommend Excel). Provide the resulting regression model? Assume an alpha of 0.05. 2a) Is the regression formula significant and why? 2b) How much of the variation in Final Grade is explained by the independent variables? 2c) If you were forced to limit your independent variables to only two variables, which would you discard and why? 2d) Predict the score for a student with the following characteristics: i. received no online help ii. read 5 books iii. attended 15 classes Ans. 2a) Ans. 2b) Ans. 2c) Ans. 2d) Ans. 1) Place Regression output here Model here A friend that runs a not-forbility of a particular course-ife skill. Student data related to s, and 2) E-books viewed by udents is shown in the table, and Place the results below. Use an alpha of 0.05. you discard and why? obs 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 ONLINEHELP? No No No Yes No Yes No Yes Yes No No No No Yes No No No No No Yes Yes Yes No No No No Yes Yes Yes No Yes No No No Yes Yes No No Yes No BOOKS 0 1 0 2 4 4 1 4 3 0 2 1 4 1 0 1 3 0 1 4 4 0 2 3 1 0 3 3 2 2 3 2 2 3 4 4 3 1 2 0 ATTENDED CLASSES 9 15 10 16 10 20 11 20 15 15 8 13 18 10 8 10 16 11 19 12 11 19 15 15 20 6 15 19 14 13 17 20 11 20 20 20 9 8 16 10 FINAL GRADE 45 57 45 51 65 88 44 87 89 59 66 65 56 47 66 41 56 37 45 58 87 64 97 55 51 61 69 79 71 62 87 54 43 92 83 94 60 56 88 62 Final Prob6.) I have been advised by my doctor to exercise more. Each day I do stomach crunches to strengthen my cor to your health. I go to the gym twice a day--morning and afternoon. The number of daily crunches I perform are record morning I am the only person in the gym; in the afternoon there are many people, and an observant trainer always give passes by. One day she asked me if the talk was a transformative moment in my exercise program. I try not to laugh, b appropriate test of hypothesis to determine the answer to her question. Use the data provided and use a level of signi (The only difference in my exercise in the a.m. and p.m. is the talk.) 1a) Perform a test to determine if the inspirational talk has made a significant difference in performance. Also, what te 1b) State the hypothesis for the test. 1c) What is the result--reject or not reject null hypothesis? Ans. 1b) Ans. 1c) Ans. 1a) Place results of test here runches to strengthen my core...a weak core can be disastrous crunches I perform are recorded over a monthly period. In the n observant trainer always gives me an inspirational talk as she program. I try not to laugh, but then think that I can use an ovided and use a level of significance of 0.05 and do a 2-tail test. in performance. Also, what test did you use? Place results of test here Day of Month A.M. Crunches 1 145 2 109 3 117 4 134 5 124 6 121 7 100 8 108 9 129 10 111 11 137 12 129 13 127 14 142 15 126 16 113 17 124 18 107 19 116 20 124 21 108 22 139 23 131 24 126 25 129 26 114 27 133 28 140 29 113 30 142 P.M. Crunches 151 115 119 136 129 127 106 112 134 121 137 135 121 156 132 117 130 124 120 128 102 133 134 132 123 120 117 144 107 148 Final Prob7.) One late Friday afternoon your obnoxious boss comes into your office as you are about to leave, and sho 26 observations that he believes to be related. Y, he believes, is the dependent variable and X1 is the independent var He also thinks there is a 2nd order polynomial relationship in the data ( Y = B 1X1 +B2X12 + B0 ), and, as you casually vie data, you tend to agree. He insists that the determination of B 1, B2 and B0 is far more important than your Friday afte gathering of young-urban-millennial-professionals (YUMPS) at a local watering hole. So, you perform the analysis usin scatter diagram and Trendline tool in Excel. Then you quietly exit for the YUMPS gathering. Now, it is Monday morning. You want to use the assumption of a 2nd order polynomial to find the exact values of B 1, . (Hint: generate a new variable that fits the assumed polynomial model and then use the regression tool in Excel) 1) Use a regression tool in Excel to determine the exact values of B 1, B2 and B0 . 2) Is the regression model significant? Use alpha 0.05. Ans. 2) Ans. 1) Place results of test here e about to leave, and shows you X1 is the independent variable. ), and, as you casually view the ant than your Friday afternoon perform the analysis using the nd the exact values of B 1, B2 and B0 gression tool in Excel) X1 Y 68,067 70,103 76,370 86,686 86,759 91,805 92,306 93,731 100,913 102,199 109,399 113,430 118,133 122,820 123,417 123,054 127,860 132,868 131,160 132,132 132,583 136,859 140,562 144,594 141,493 139,465 ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ###