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Year TN GDP VA GDP Problem 2 Tri-Cities' Retail Sales, mil. $'s, 2012 - 2016 Problem 1 Problem 4 Problem 5 1 202976 294126 Q1
Year TN GDP VA GDP Problem 2 Tri-Cities' Retail Sales, mil. $'s, 2012 - 2016 Problem 1 Problem 4 Problem 5
1 202976 294126 Q1 Q2 Q3 Q4 Total Year Retail Sales PI Year Enroll. Tuition
2 213093 308784 1721.5 1774.1 1751.5 1844 7091.1 1 6305 16045.88 2009 214 10514.57
3 219514 323570 1666.4 1799.7 1747.1 1846.1 7059.3 2 6583 16404.68 278 9002.899
4 221830 336195 1675.8 1826.9 1835 1941.9 7279.6 3 6977 17422.75 275 9122.211
5 222160 346918 1719.7 1952.5 1945 2032.3 7649.5 4 7091 18061.93 265 9249.264
6 229019 349495 1812.2 1991.6 2003.7 2097.4 7904.9 5 7059 17813.47 278 9072.022
7 236620 362386 7280 18188.52 238 10152.44
8 246938 376770 7649 18664.57
9 250834 396319 Your Company Sales, mil. dols., 2010 - 2017 Problem 3 7905 18980.04 2016
10 256809 405682 Q1 Q2 Q3 Q4 Total Year
11 254269 408148 48.6 54.2 59.8 70.8 233.4 1
12 255826 407227 49.5 56 63.5 85.5 254.5 2 Problem 6
13 246541 407302 54.7 59.9 65 89 268.6 3 PriceDif AdvExp Sales Y
14 250261 416903 57 63.9 68.6 94.2 283.7 4 0.05 5.5 7.38
15 257138 419724 58.7 67.1 74.2 102.8 302.8 5 -0.25 6.75 8.51
16 265211 422269 65.3 72.3 78.3 111.2 327.1 6 -0.6 7.25 9.52
17 269453 422275 68 80 85 115 348 7 0 5.5 7.5
18 273748 422546 73 86 90 123 372 8 -0.25 7 9.33
19 282251 432742 -0.2 6.5 8.28
20 287776 435192 -0.15 6.75 8.75
-0.05 5.25 7.87
0.15 5.25 7.1
-0.15 6 8
-0.2 6.5 7.89
-0.1 6.25 8.15
-0.4 7 9.1
-0.45 6.9 8.86
-0.35 6.8 8.9
-0.3 6.8 8.87
-0.5 7.1 9.26
-0.5 7 9
-0.4 6.8 8.75
0.05 6.5 7.95
0.05 6.25 7.65
0.1 6 7.27
-0.2 6.5 8
-0.1 7 8.5
-0.5 6.8 8.75
-0.6 6.8 9.21
0.05 6.5 8.27
0 5.75 7.67
-0.05 5.8 7.93
-0.55 6.8 9.26
5. These data show new student enrollment (Enroll) at a small college and discounted annual tuition (Tuition).
a. How would new student enrollment change if the discounted tuition is lowered by $1,000?
b. Predict enrollment if Tuition = $8,200.
6. These data show unit sales of Product Y (Sales Y), the price difference between Product Y and a competitors product (PriceDif) and advertising expenditures to promote Product Y (AdvExp). Unit sales are in hundreds of units, PriceDif is in dollars and AdvExp is in hundreds of dollars.
Develop a multiple linear regression equation to:
a. Predict Sales Y when PriceDif is $0 and AdvExp is 8.
b. Predict the change in sales when AdvExp increases by 2, other things equal.
Year TN GDP VA GDP Problem 2 Tri-Cities' Retail Sales, mil. $'s, 2012 - 2016 Problem 1 Problem 4 Problem 5
1 202976 294126 Q1 Q2 Q3 Q4 Total Year Retail Sales PI Year Enroll. Tuition
2 213093 308784 1721.5 1774.1 1751.5 1844 7091.1 1 6305 16045.88 2009 214 10514.57
3 219514 323570 1666.4 1799.7 1747.1 1846.1 7059.3 2 6583 16404.68 278 9002.899
4 221830 336195 1675.8 1826.9 1835 1941.9 7279.6 3 6977 17422.75 275 9122.211
5 222160 346918 1719.7 1952.5 1945 2032.3 7649.5 4 7091 18061.93 265 9249.264
6 229019 349495 1812.2 1991.6 2003.7 2097.4 7904.9 5 7059 17813.47 278 9072.022
7 236620 362386 7280 18188.52 238 10152.44
8 246938 376770 7649 18664.57
9 250834 396319 Your Company Sales, mil. dols., 2010 - 2017 Problem 3 7905 18980.04 2016
10 256809 405682 Q1 Q2 Q3 Q4 Total Year
11 254269 408148 48.6 54.2 59.8 70.8 233.4 1
12 255826 407227 49.5 56 63.5 85.5 254.5 2 Problem 6
13 246541 407302 54.7 59.9 65 89 268.6 3 PriceDif AdvExp Sales Y
14 250261 416903 57 63.9 68.6 94.2 283.7 4 0.05 5.5 7.38
15 257138 419724 58.7 67.1 74.2 102.8 302.8 5 -0.25 6.75 8.51
16 265211 422269 65.3 72.3 78.3 111.2 327.1 6 -0.6 7.25 9.52
17 269453 422275 68 80 85 115 348 7 0 5.5 7.5
18 273748 422546 73 86 90 123 372 8 -0.25 7 9.33
19 282251 432742 -0.2 6.5 8.28
20 287776 435192 -0.15 6.75 8.75
-0.05 5.25 7.87
0.15 5.25 7.1
-0.15 6 8
-0.2 6.5 7.89
-0.1 6.25 8.15
-0.4 7 9.1
-0.45 6.9 8.86
-0.35 6.8 8.9
-0.3 6.8 8.87
-0.5 7.1 9.26
-0.5 7 9
-0.4 6.8 8.75
0.05 6.5 7.95
0.05 6.25 7.65
0.1 6 7.27
-0.2 6.5 8
-0.1 7 8.5
-0.5 6.8 8.75
-0.6 6.8 9.21
0.05 6.5 8.27
0 5.75 7.67
-0.05 5.8 7.93
-0.55 6.8 9.26
6. These data show unit sales of Product Y (Sales Y), the price difference between Product Y and a competitors product (PriceDif) and advertising expenditures to promote Product Y (AdvExp). Unit sales are in hundreds of units, PriceDif is in dollars and AdvExp is in hundreds of dollars. Develop a multiple linear regression equation to: a. Predict Sales Y when PriceDif is $0 and AdvExp is 8. b. Predict the change in sales when AdvExp increases by 2, other things equal.
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