Chat with us, powered by LiveChat Activity I - Last year, your firm collected data on each of its 107 division managers. The data contain growth figures for each manager's division, the manager's tenure with the | Wridemy

26 Jan Activity I – Last year, your firm collected data on each of its 107 division managers. The data contain growth figures for each manager’s division, the manager’s tenure with the

Posted at 06:27h in Business & Finance by

 Activity I – Last year, your firm collected data on each of its 107 division managers. The data contain growth figures for each manager's division, the manager's tenure with the firm, and the manager's score on a leadership test, which was administered firmwide. These data are contained in the file attached.

  1. Run a regression designed to determine the effect of manager tenure on division growth.
  2. What role, if any, can the manager's leadership test score play in the regression you ran for Part a? Explain.

Activity II – Use the data in the attached for this question.

You are working as an analyst for a large cable company that offers bundles of channels all across the United States. One of the bundles is the “basic package,” which includes network channels along with a few other basic cable channels. You are interested in learning how the price of this basic package influences the rate of subscriptions in a market. You have data on subscriptions per 1,000 local residents, price for the basic package, and average local household income. You also have data on local telecom labor costs per subscriber. You believe this last variable influences the local price but not subscriptions per se.

  1. Based on the data provided, write out an expression for the data-generating process for subscriptions per 1,000 local residents.
  2. Estimate the effect of basic package price on subscriptions per 1,000 local residents using OLS. Why might you distrust this result as being a causal effect?

Sheet1

Growth Tenure Test Score
4 6 14
6 7 63
3 16 19
5 4 48
9 26 100
3 25 13
5 9 86
2 9 89
4 17 13
1 24 83
3 4 41
11 16 59
7 26 107
4 10 91
5 9 79
9 25 27
7 11 96
10 4 46
0 14 32
-1 13 40
2 1 11
9 26 98
5 30 91
3 2 6
6 12 8
5 23 66
4 10 42
12 20 102
3 19 50
4 19 18
7 19 46
2 7 41
7 21 40
9 8 74
7 24 54
3 22 13
2 15 60
3 14 58
9 24 33
0 5 20
6 15 107
5 11 24
7 8 67
7 4 54
9 21 56
5 13 57
6 13 64
1 5 9
6 25 94
1 22 11
4 9 28
4 18 97
6 16 41
12 27 77
10 25 73
9 27 78
8 18 70
3 15 75
1 14 14
11 13 60
11 27 104
8 19 54
1 13 20
7 21 61
5 12 34
3 5 6
7 11 55
6 29 66
7 20 47
8 10 20
9 8 90
7 11 100
2 2 25
7 18 85
7 18 101
9 7 99
7 30 95
5 10 52
7 12 67
7 8 55
3 17 17
9 17 92
10 23 104
8 24 36
5 6 27
9 22 67
6 26 99
12 22 94
5 24 75
6 5 30
4 28 101
2 10 88
-2 6 9
11 24 81
9 7 101
2 21 11
5 28 51
2 11 102
2 21 60
1 2 11
10 11 101
10 24 79
9 19 100
6 13 94
14 18 107
2 25 58
2 6 72

,

Sheet1

Subs per 1000 Price Income Labor
440.7088560406 41.9736426734 67.867 12
475.0794335609 41.4217389268 64.549 6
426.013408628 36.224901438 53.664 6
437.3416206739 45.6521034457 60.429 12
424.3132452812 40.6073742135 52.669 8
405.8547973626 29.8266328938 60.895 6
392.3133086757 40.3683847793 61.103 15
477.0864376661 50.3749062777 65.837 12
487.1057145355 49.3809524226 56.82 8
488.8287286504 50.3002881084 68.027 9
489.1651805929 46.8303634322 55.183 8
517.7953709658 48.8980618276 62.407 6
508.5574656594 57.2917442766 66.807 13
455.5854771951 48.6299128659 62.806 12
442.4767970965 49.9781328494 53.608 13
452.0480126306 44.1163354384 59.35 11
505.8553431506 48.0017238584 64.845 7
424.0854643019 43.587410717 53.561 12
450.9913706579 49.8445617763 57.924 13
440.1421516895 49.6698586149 64.123 14
458.4030341013 38.5660056836 60.007 6
524.0989899155 50.3169983193 67.197 7
449.6943836438 44.277397274 52.03 9
473.3537491048 44.8719581841 63.122 7
440.6714647857 38.6295774643 63.894 6
460.3150733765 47.3636788961 56.133 12
463.3133672025 40.4573945337 68.569 7
483.3185747802 53.26842913 64.708 13
485.182586227 45.0945977045 63.615 6
455.6776429492 53.6777738249 61.611 15
444.9937570251 37.2276261708 54.628 6
458.1288704425 45.7286450737 60.757 11
455.5963424942 49.2550570824 68.066 14
542.7305048484 54.3710841414 60.504 5
464.580054209 44.3266757015 55.62 6
451.3592228654 48.7102038109 62.098 15
501.7435013321 45.484250222 66.838 6
496.0710398957 52.3838399826 58.768 10
528.0587312932 52.3894552155 62.722 6
503.9196202184 54.5032700364 56.9 9
447.3272048757 42.927534146 55.762 10
472.0317233279 50.3032872213 57.212 12
467.9481011125 51.1880168521 51.82 12
512.8771417729 56.2321902955 65.484 11
462.8304808295 43.1750801383 52.78 5
457.3451212344 51.5681868724 50.936 15
452.2986256655 49.5616042776 64.929 15
403.7495936667 42.1057656111 61.115 14
457.4643150574 38.8492191762 67.369 5
439.6837280845 42.2569546808 49.142 7
427.1804167438 38.3369027906 53.159 9
436.1152505275 45.9728750879 63.278 14
463.4571323993 52.7301887332 54.076 14
469.2879976081 52.2009996014 54.082 12
469.6511059452 44.2333509909 70.251 7
463.3870350382 39.5905058397 66.844 7
540.5173261432 55.1742210239 54.472 7
494.7101661845 55.8745276974 59.463 13
519.1608018812 63.3934669802 61.8 15
449.3304619219 45.9252436536 60.779 10
426.4762936441 43.6215489407 60.747 14
470.9543456424 44.0927242737 54.398 7
486.1558391561 53.0344731927 52.949 11
428.2706986331 48.8472831055 56.187 15
475.3330935213 56.7250155869 62.983 15
450.2224818009

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