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To decide in what zone should be placed a store which sells video-cassettes, the manager of a firm which sells and rents cassettes makes a study to estimate the demand for each store. The independent variables are: number of inhabitants, average income of inhabitants, number of competitors situated (all these variables refer to a one mile distance) and the price of a video-cassette. You will have a number of 15 supermarkets and the values of all 5 explicative variables. The data are given below:
Demand (yi)
No. of inhabitants (x1i)
Income (x2i)
Competitors (x3i)
Price (x4i)
323.581
5.556
42.746
3
2.49
343.682
5.917
43.106
2
2.99
375.264
5.483
46.993
5
351.242
6.400
43.249
1.99
328.417
40.695
318.069
6.683
41.253
330.959
6.065
40.791
267.236
7.491
39.932
320.883
6.284
36.826
1
409.535
5.851
45.300
316.262
5.681
42.645
351.806
5.187
42.306
333.655
6.164
44.842
372.679
7.320
45.233
362.796
5.062
41.426
Questions:
1. What can you say about R and R-squared?
2. How do you interpret the standard error?
3. Explain briefly the meaning of the F-test and interpret its value
4. For which variables did you obtain a significant coefficient? Interpret all the coefficients from an economic point of view
5. Which variables you would eliminate if you were to re-do the estimation?
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A company produces 2 modules of mobile phones. 1.Basic modle is sold 5000/=, direct material cost 1250/=, requires 0.25h labour time. Produce unites 8000 per month. 2.smart model
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