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A large sports supplier has many stores located world wide. A regression model is to be...

A large sports supplier has many stores located world wide. A regression model is to be constructed to predict the annual revenue of a particular store based upon the population of the city or town where the store is located, the annual expenditure on promotion for the store and the distance of the store to the center of the city.

Data has been collected on 30 randomly selected stores: (AT BOTTOM)

Find the multiple regression equation using all three explanatory variables. Assume that x1 is population, x2 is annual promotional expenditure and x3 is distance to city center. Give your answers to 3 decimal places.

a) y^ = BLANK + BLANK population + BLANK promo. expenditure + BLANK dist. to city

e)The value of R2 for this model, to 3 decimal places, is equal to

f)The value of s for this model, to 3 decimal places, is equal to

g)Construct a new multiple regression model by removing the variable distance to city center. Give your answers to 3 decimal places.

The new regression model equation is:

y^ = + population + promo. expenditure

At a level of significance of 0.05, the result of the F test for this model is that the null hypothesis A) Is B) is not rejected.

c)The explanatory variable that is most correlated with annual revenue is:

population
promotional expenditure
distance to city

d)The explanatory variable that is least correlated with annual revenue is:

population
promotional expenditure
distance to city

H) In the new model compared to the previous one, the value of R2 (to 3 decimal places) is:

increased
decreased
unchanged

i)In the new model compared to the previous one, the value of s (to 3 decimal places) is:

increased
decreased
unchanged

Annual revenue ($)
(× 1000)
Population
(× 1000)
Annual promotional
expenditure ($)
(× 100)
Distance to
city center (mi)
195 124 142 19
104 90 64 9
294 459 138 6
316 667 95 19
228 189 158 18
406 849 74 7
247 284 177 19
204 267 113 19
60 46 100 9
539 918 172 15
575 942 175 8
326 677 90 14
275 479 129 1
470 834 168 1
308 435 129 5
318 475 178 7
512 915 95 18
153 183 173 11
219 266 134 16
443 687 197 15
225 177 184 1
233 192 185 18
303 612 93 5
507 981 93 16
487 923 138 2
432 963 44 17
180 138 165 10
448 820 55 11
461 719 156 10
97 48 115

19

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