Signature Assignment

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Assignment Content

Purpose of Assignment 

The purpose of this assignment is for students to synthesize the concepts learned throughout the course. This assignment will provide students an opportunity to build critical thinking skills, develop businesses and organizations, and solve problems requiring data by compiling all pertinent information into one report. 

Resources: Microsoft Excel®,

Signature Assignment Databases

,

Signature Assignment Options

,

Part 3: Inferential Statistics

Scenario: Upon successful completion of the MBA program, imagine you work in the analytics department for a consulting company. Your assignment is to analyze one of the following databases:

· Manufacturing

· Hospital

· Consumer Food

· Financial 

Select one of the databases based on the information in the Signature Assignment Options. 

Provide a 1,650-word detailed, four-part, statistical report with the following sections:

·

Part 1 – Preliminary Analysis

· Part 2 – Examination of Descriptive Statistics

· Part 3 – Examination of Inferential Statistics

· Part 4 – Conclusion/Recommendations 

Part 1 – Preliminary Analysis

Generally, as a statistics consultant, you will be given a problem and data. At times, you may have to gather additional data. For this assignment, assume all the data is already gathered for you.

State the objective:

· What are the questions you are trying to address?

Describe the population in the study clearly and in sufficient detail:

· What is the sample?

Discuss the types of data and variables:

· Are the data quantitative or qualitative?

· What are levels of measurement for the data? 

Part 2 – Descriptive Statistics 

Examine the given data.

Present the descriptive statistics (mean, median, mode, range, standard deviation, variance, CV, and five-number summary).

Identify any outliers in the data.

Present any graphs or charts you think are appropriate for the data.

Note: Ideally, we want to assess the conditions of normality too. However, for the purpose of this exercise, assume data is drawn from normal populations. 

Part 3 – Inferential Statistics

Use the Part 3: Inferential Statistics document.

· Create (formulate) hypotheses

· Run formal hypothesis tests

· Make decisions. Your decisions should be stated in non-technical terms.

Hint: A final conclusion saying “reject the null hypothesis” by itself without explanation is basically worthless to those who hired you. Similarly, stating the conclusion is false or rejected is not sufficient. 

Part 4 – Conclusion and Recommendations

Include the following:

· What are your conclusions?

· What do you infer from the statistical analysis?

· State the interpretations in non-technical terms. What information might lead to a different conclusion?

· Are there any variables missing?

· What additional information would be valuable to help draw a more certain conclusion?

Format your assignment consistent with APA format.

Plagiarism Free 

2

>Option

1

– Manufacturer

1

3

0

7

1

2

4

7

1

6

2

1

204

0

6

0

07

1

30

1

40

74

3

1

207 26

8

6

1

3

72

10

21

1

1

8

12

5

1

21 15

2

7

2

3 2

7

42 2

2 2

8

2

6 4

2

2

52

3

222 74 63

07

57

7

3

13 12

1

3

17 13

7

3

9

21

3

3

55 44

3

76

06

4

3

61 47

3

27 22

4

6

4

45

7

4

38 32

6

2

4

17 14

9

4

34 28

3

450 4

1 1 34 71 17 4

31 25

5

4

224

3

76

7

4

83 68

5

1

5

147

5

209

4

32

5

51 43

9

5

68

6

5

94 78

5

64

80

5

6

70 53

1

6

37 29

447 6

81 61

5

6

6

54 39

8

6

15 11

7

90

7

55 42

5

7

212

68

7

267 232 182

63

7

92

3

8

272 121 16

82

8

273 136 57

7

6

8

274 69 25

3

8

604

07

72

8

276 41 28

8

1

8

21 12

9

577 8

65 50

504 8

279 55 39

8

236 8

281 80 45

67

98

9

282

79

96

9

283 213 106

13

3

9

126 75

1

32

9

285 51 28

9

126 75

86

5

9

37 24

77

30

9

289 76 45

7

5

9

291 67 43

6

80

18

10

295 25 18

4

10

14 8

10

65 54

11

8 7

11

61 46

7

11

306 122 95

1

11

308

598

21

74

11

15 12

3

404 12

313 3 2

163 35 12

314 37 31

7

2

716 12

2 2 53 85 62 12

6 4

199 12

8 7 328

75 12

7 6 233

40 12

321 12 9

7

282 13

60 51

7

13

64 50

13

17 13

13

325 31 25

7

13

45 36

600 13

327 205

39

0

6

13

328 17 13

263 13

329 72 53

13

221

96

14

106

14

35 26

14

15 11

694 14

162 123

70

2

14

94 79

14

32 23

14

33 27

9

3

15

140 107

50

4

15

45 32

3527

15

432 315

4

15

345 104 81

15

346 259

31

15

129 99

15

40 24

15

300 219

8

15

79 55

9

16

352 94 70

8

16

353 205

8

16

354 295 211

43

16

355 192 110

1

16

356 265 172

8

16

259 96

5

7

7

16

201 147

16

16

74 51

5

17

171 120

17

87

17

364 157 117

28

5

17

49 37

1

17

120

1

17

367

17

106

20

17

634

9

52

18

377 190

4

18

373 141 108

0

18

31 23

18

18 14

4

412 18

81 29

18

47 35

18

381 186 68

19

272 141

19

384

157

51

19

27 17

19

61 36

2290 19

387 6 4

382 177 19

43 30

20

13 10

506 328 20

76

4

20

395 35 26

20

24 19

997 415 20

399 179 123

9

20

SIC Code No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials End Yr. Inven. Indus. Grp.
2

0 4 3 3

7 23 5 1

8 78 13 3

6 30
20 1

31 83 15 72 42 74 31

57
203 204 1

6

9 2

4

50 27 22 87 32
10 70 21 67 37 40 34
205 220 137 207 12 120 1

1

55
206 89 69 1

26 1

36 3

61
18 4

25 19 130 1

94
208 14 3

52 3

35 71 99
209 17 126 20

54 1

96 313
2

11 23

44 555 5

506
212 28 1

63
213 150 314 155
214 6

24 2

62 554
221 47 2471 4

219 9

29
43 53 142
223 6

73 106 325
224 81 707 267
225 16 147 89

86 104 2083
226 51 41 31

45 4

140 6

97
227 40

76 7

125 14

46
228 84 38 8994 101
229 4

276 5

504 1

2

91
231 1

2

39 716 3

56
232 200 178 9423 8

92 2314
2

33 294 250 110 11

121 272
234 191 2

283 68
235 59 3

64 197
236 2063 181
237
238 144 1

321 526
239 1

79 10

60 123 274
241 5

77 9

66 578
242 172 10

404 19

2

85 3979
243 257 1

327 186 3

329
244 1

90 2

170 355
245 82 460 7290 5

80
2

49 5518 8

135 1

604
251 273 233 124 129 353
252 5

447 401 829
253 2290 5101
254 4

182 3

75 95
259 281 2

694 718
261 2201 3

279 725
262 116 1

88 48 20

596 4257
263 9

65 10604 1

502
265 163 156 24

634 3976
25918 289 5427
271 403 136 306 848 894
179 6940 1

216
1

785 8863 373
9

699 282 874
275 437 384 295 4

300
387 381 688
277 3

98 1047
278 4388 2055
4055 109
165 112 2644
115 25025 345 6

192
598 27

187 1

153
284 3

180 199 4

535
8497 9849 2178
286 288 46

93 8577
287 122 111 2

354
1

154 1

308 2749
2

600 1

328 107
346 6182 6

58
299 2187 4446 670
301 7079 7091 1067
302 442 496 175
305 4528 3805 105
7275 7

195 141
763 556 57264 118
311 131 1865
162
190 168
315
316 747 395
317 255
319 177
171 943
322 6532 352 1

505
323 4850 4254 883
324 3

509 2282 828
2

176 138 700
326 2696 1

183
152 157 1

701 196
999 565
7

838 5

432 1652
331 174 29180 456 12

198
332 128 9061 6913 1543
333 4200 11

184 1

834
334 1410 5

735
335 166 3

189 6

377
336 5856 4696 938
339 3

164 2

790 800
341 399 9

364 145
342 117 8720 312
343 4

412 1121
344 2

797 31527 7204
6

936 4909 1768
211 19880 215 3

997
347 7

793 6232 1181
348 3528 1689 1077
349 2171 19273 6460
351 10513 12

954 367
9

545 1

185 3339
133 1

817 23474 7344
22673 143 6730
1

922 16515 6823
23110 18543 789
357 4

113 60857 102
358 17521 2

1819 4857
359 392 293 25322 13897 4964
361 6700 5

523 149
362 14278 12657 3887
363 108 9

466 1

2578 2299
134 1106 3076
365 3459 762 1070
366 258 38705 2

959 9467
588 368 84059 44486 13145
369 151 139 13

398 3

514
371 772 10

589 223639 158
372 45220 42367 3681
7903 776 2165
374 2590 4363 1233
375 1435 167
376 9986 8120 4770
379 3564 5476 1102
2

1071 8760 6183
382 29028 18028 7681
268 310 16787 7761
385 2

390 1020 426
386 14032 8

114
415
391 2761 3646 1

451
393 685
394 103 8327 660 2608
2643 1789 799
396 1406
1

119 8530 2861

Option 2 –

Hospital

Hospital

1 1 2 1 107 312

2 1 1 1 198 1077

3 1 2 1 356 1027

4 1 1 1

355 328

5 7 1 1 9 168 181
6 4 2 1

1077

7 4 4 1 65 735

8 4 2 1 48 1 131
9 1 2 1 253

3

10 1 1 1 21 257 233
11 1 1 1 27

241

12 6 3 1 30

203

13 6 3 1 43 0 325
14 6 2 1 233

15 6 4 1 2 211 347
16 6 1 1 11 16 79
17 6 3 1 84

505

18 6 2 1 219

1543

19 6 3 1 112

5

20 6 3 1 124 0 959
21 6 3 1 50

325

22 6 2 1 142

954

23 6 2 1 111

24 6 1 1 140

25 6 3 1 28 451 300
26 6 2 1 154 1689

27 6 2 1 150

28 6 3 1 144

29 6 3 1 42

354

30 6 2 1 77

31 5 2 1 119

32 5 2 1 27

386

33 5 2 1 15 126 144
34 2 2 1 179

6

35 2 2 1 175

36 2 2 1

37 1 3 2 32 0 96
38 1 2 1 74 0

39 1 1 1

40 1 2 1 253

41 1 3 1 180

1071

42 1 1 1 184 762

43 1 2 1 243

44 1 2 1 115 496 670
45 1 1 1 215

46 1 3 2 48 0 167
47 1 3 1 124

793

48 1 2 1 189

9

49 1 1 1 181 113 316
50 1 1 1 9 0 93
51 1 3 1 28 0 373
52 1 2 1 288 173 263
53 1 1 1 108

943

54 1 2 1 154

55 7 2 1 76

596

56 7 3 1 165

57 3 1 2 295 0

58 3 3 1 101 0

59 3 2 1 69

60 3 2 1 12 99 136
61 3 2 1 185

62 3 2 1

63 3 2 1 114

64 3 3 2 49 0 243
65 3 2 1 106

66 3 2 1 460

1

67 3 2 1 43 126

68 3 4 1 29 556

69 3 2 1 125

7

70 3 2 1 17 415 322
71 3 1 1 10 216 185
72 3 3 1 14 339 205
73 3 1 1 173

74 3 2 1 207

75 3 2 1 223 790

76 3 2 1 82

77 3 1 1 64 35 156
78 3 2 1 139

79 3 2 1 109 793

80 3 1 2 298 0 790
81 3 3 1 52 0 308
82 3 1 1 34 14 70
83 3 1 2 168 0 494
84 3 3 2 21 0 111
85 1 4 1 390 0

86 1 1 1 47 0 244
87 1 2 1 80 776 525
88 1 3 1 50 451

89 1 3 2 113 0 94
90 1 2 1 45 145

91 1 1 1 76

92 1 3 1 129 1 234
93 2 2 1 60 319 401
94 2 2 1

95 2 2 1 17 295 198
96 2 2 1 138 496

97 2 2 1 64 589 545
98 2 2 1 62

99 2 1 1 131 701

100 2 2 1 265

101 3 4 2 456 0

102 3 2 2 40 0 126
103 3 1 1 310

104 3 3 1 72 0 251
105 3 3 2 19 0 85
106 3 4 1 112 0 432
107 3 1 2 375 0

108 3 3 2 15 0 66
109 3 2 1 78

556

110 3 1 1 123 169 347
111 3 2 1 54 66 239
112 3 2 1 96

113 1 3 1 82

114 1 1 2 1106 0

115 1 1 1 30 0 102
116 3 1 2 56 0 262
117 3 4 1 36 342 885
118 3 3 1

494

119 3 1 2 180 0

120 3 4 1 59 0 330
121 5 2 1 127 0

122 5 1 1 37 0 75
123 5 4 1 13 286 262
124 5 2 1 100 235 328
125 3 3 1 47 339 377
126 3 1 1 194 398

127 3 2 1 172

128 5 3 1

129 5 3 1 120

130 5 1 1 179 714

131 2 4 1 140 0 535
132 2 3 2 78 0

133 2 3 2 68 0 202
134 2 2 1 186

135 2 2 1 91 0

136 2 1 1

137 5 1 1 254

138 5 2 1 108 1071 815
139 5 2 1 61 352

140 2 2 1 174 254 502
141 2 1 2 306 0

142 2 3 2 28 0 50
143 2 2 1 395 699

144 2 2 1

145 2 1 1 335

146 1 2 1 46 0 68
147 1 1 1 316

1 4 2

0

149 1 1 1 74 339 576
150 1 2 1 86 130 284
151 3 2 1 38 91 145
152 3 2 1 147

153 3 4 2 232 0

154 3 1 2 138 0 336
155 3 2 1 38 509 415
156 3 2 1 245

157 3 1 2 171 0

158 3 3 1 51 447

159 3 4 1 28 1161 437
160 3 1 2 797 0 261
161 7 2 1 56 922

162 7 1 1 69

163 7 1 1 40 78 61
164 7 4 1 163 0

165 7 2 1 231

166 2 1 2 523 0

167 2 4 1 31 0

168 2 2 2 43 0 153
169 2 2 1 66

170 2 2 1 231 1165

171 1 4 1 11 466

172 1 3 1 144 1106 789
173 1 3 1 43 376 395
174 3 4 1 185 0

175 3 2 1 82

362

176 1 2 2 49 0 144
177 1 3 1 24 352 229
178 1 3 1 63 447 396
179 1 2 1 274

180 1 3 1 93

181 1 4 1 86

182 1 3 2 28 0 102
183 1 3 2 25 0 106
184 1 3 1 181

185 5 3 1 39

392

186 5 1 1 302

187 5 2 1 80

785

5 2 1 63 2171 607

189 2 2 1 31 364 273
190 2 2 2 170 0

191 1 1 1 203

192 1 2 1

0

193 1 3 1 83

583

194 7 2 1 84

514

195 7 1 1 29 387 216
196 7 2 1 187

197 7 2 1 77 545

198 5 1 2 104 0 399
199 5 1 1 85 838 834
200 5 1 1 47 51 104
Geog. Region Control Service Census Births Personnel
792
1762
2310
100
159 3810
742
173 1594
169
430
2049 676
2648
2450
146 755
1993
2275
1

494 1091
1313 671
753
1

583 607
2017 929
995
2045 408
1686 1251
503
202 2047
1412 1343
461 1517 1723
529
414 2719 3694
1074 1042
1421
1

525
3

194 1983
1442 1653
1107
298 841
1064
759 605
1317
1751 1165
568
507
714 479
2243 1456
378 3

966 3486
1308 885
2514 1001
3714 330
337
1

193
132 1

161
1217 1224
2641 1704
815
520 712
1168 1769
875
1618
472
297
1284 847
418 2154 3928
1231
806 663
820
3968 2581
1298
3655 2534
864
3063
827 973
570 439
1849
127 549
611
1471
575
1275 1916
516 5699 2620
1364 571
703
160
779 1330
370
340 2202 3123
3346 2745
576
808
728
923 2462 4087
3311 3012
4207 3090
148 416 1358
1143 2312
1124
1026 1779
338
453
609
562 647
2074
2122 2232
948
409
710 741
1625
538
956
637
1227 2256
963 731
3038 1477
868 939
1189
2849 3516
1728
188
630
2993 1379
296 1108
1964
601
1946 1593
1055

Option 3 – Consumer Food

1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 1

8

7

1 1

1 1

3805

1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 1

5

1 1

1 1

1 1

1 1

1 1

1 1

1 1

2

0 1 1

1 1

1 1

4

1 1

0 1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 1

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

1 2

9551

2 1

2 1

2 1

2 1

2 1

0 2 1

2 1

2 1

2 1

2 1

7204

2 1

2 1

3

2 1

0 2 1

7761

2 1

2 1

2 1

936 2 1

2 1

2 1

3

2 1

2 1

2 1

2 1

2 1

2 1

2 1

9

2 1

2 1

2 1

6

2 2

146 2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

2 2

3 1

3 1

3 1

9522

3 1

3 1

3 1

3 1

3 1

3 1

817 3 1

3 1

3 1

3681

3 1

3 1

3 1

6314

3 1

3 1

3 1

9093

3 1

3 1

3 2

3 2

9286

3 2

1

3 2

3 2

3 2

3 2

3 2

3 2

3 2

5188

3 2

3 2

3 2

3 2

3 2

240 3 2

0 3 2

3 2

3 2

0 3 2

4 1

4 1

4 1

4 1

4 1

4 1

8185

4 1

4 1

4 1

4 1

4 1

4 1

7436

4 1

4 1

4 1

4 1

4 1

4 1

4 1

4 1

4 1

4 1

4 1

9

4 1

4 1

4 1

6426

4 1

5839 4 1

4 1

4 1

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

4 2

9908

4 2

Annual Food Spending ($) Annual Household Income ($) Non mortgage household debt ($) Region: 1 = NE 2 = MW 3 = S 4 = W Location: 1 = Metro 2 = Outside Metro
8909 56697 23180
5684 35945 7052
10706 52687 16149
14112 74041 21839
13855 63182 18866
15619 79064 21899
2694 25981 8774
9127 57424 15766
13514 72045 27685
6314 38046 8545
7622 5

240 2805
4322 41405 6998
29684 4806
6674 49246 13592
7347 41491 4088
2911 26703 15876
8026 48753 16714
8567 55555 16783
10345 71483 21407
8694 50

980 19114
8821 46403 7817
8678 51927 1441
14331 84769 17295
9619 59062 16687
9286 57952 14161
8206 58355 19538
16408 81694 15187
12757 6

9522 14651
17740 9

613
7739 57796 22057
15383 88276 1896
4579 3226 7979
11679 65928
12877 69924 27330
16232 91108 9876
9621 54070 1

9908
8171 47238 17819
12128 77427 31340
8642 59805 4963
12400 60334 6632
9185 54114 18593
7862 40680 15202
9

775 58263 1486
6771 52008 21

713
3059 39643 12179
13211 70309 13221
7408 46450 5602
11581 76140 33874
14233 80833 11478
3352 31899 2762
2630 21647 2663
9093 65924 11355
12652 65923 5132
9559 62811 12613
6112 42335 3149
10431 65134 15196
12630 64621 21433
4578 36553 5502
9551 62910 11376
10262 70727 13287
57634 11857
10143 56549 16136
8955 59662 11627
10197 57350 18432
11234 56447 10871
9320 61136
9089 51526 4902
1

2300 79979 17270
11484 66733 15145
11215 75359 15611
40795 8975
5579 39128 6576
1172 75482 12508
9353 63998
45845 6671
4261 38223 8576
9830 66787 1178
12386 77852
8673 55825 14167
10944 57022 9018
9910 6426 12768
9928 75881 17423
4264 34343 21323
7971 41243 21009
8290 53021 20151
12669 66991 9250
7272 49719 20838
9784 5839 16065
9187 50477 9407
5866 39112 20409
9456 5188 11668
6270 34797
9518 62348 5201
10968 78704 17002
8865 53620 32004
9226 51577 15922
4913 34761 17704
6976 60968 17799
8152 51281 8167
2887 25013 18763
8062 59238 10815
8895 47344 11814
8444 52645 22469
6148 35309 17139
4563 34355 10612
8185 50630 21187
3391 29056 15735
7436 48721 18363
50459 16478
11290 72805 21238
10403 56954 22218
4693 39343 24696
5626 38833 14371
11869 55021 35576
13055 77605
8783 57937 18591
13031 63343 25531
36479 17950
5549 40381 14257
4108 26309 26581
41421 22470
7700 54579 29065
7479 40551 31757
50369 6404
9863 54422 24334
8043 51836 26213
9552 73600 36374
51873 29631
7987 48003 1726
3875 36519 13579
10746 75152 10659
6888 44974 23711
5479 48923 4594
6949 43769 21221
10650 75947 33357
41423 33641
5311 40189 17791
4691 36772 5829
8056 59690 19594
11304 53654 23066
8112 59067
8696 65962
5869 37254 10157
3776 33568 14143
11829 56934
13087 88822 17565
10986 59635 27863
5762 38407 18867
11617 78627 11894
9895 47710 22930
16293 64443 31687
58871 35424
13

972 87954 11549
11243 54778 12552
4635 39825 19494
10063 49536 12195
8426 60102 13787
49139 22356
11747 51052 4553
15397 70500 12025
6842 54894 16217
9678 60570 4106
12852 57625 31228
10114 56956 25907
8496 61400 1093
6689 50532 17106
15696 72774 17793
9841 69981 21607
1252 66891 17689
10210 67431 19995
8868 64782 14489
38987 17864
11096 64867
10086 50421 8689
2587 27076 17534
12492 51784 20284
8456 54135 22037
6801 53291 23342
6339 49804 34943
7802 52205 28579
9717 72841 22349
6026 46238 20165
5618 45938 10538
10217 77716 18516
8338 59711 7980
9048 42106 19786
4017 36462 9935
10906 53403 18177
15148 71290 6696
8830 66759 20972
8481 57616 28767
11358 76221 1373
10553 78202 5920
6969 55164 24795
13219 61171 21482
3543 34093 25969
7326 50647 10750
8458 59898 22940
11766 52884 25970
73629 7112

Option 4 – Financial

6

2

4

2.08

3

19

6

6

7

0.2

0.6

6

7.1

9

1.4

4

7

6

1.4

2

4

7

1.1

7

25322

3.8

5 1916

6

9

5

5

1

775

3 954 2299 2.4

7

6

8

1.1

3

1.8

1

18

1

0.16

3

2

7.7

3

1.2

2

2.08

2

16

3

12.3

1

2

6.1 0.33

3

1.8

6

12.3

0.2

7 1064 1067

7

3

12.2

1

1.3 0.2 22

2 966 613 228

4

7.9 1.18

4 10262

6.9

2

3 179 326 8.3

14

4 3226 1227

1.4

2

47

1

3

8 1.66 1.5 13.7

6 2578

14.5

1.04 13.3

5

24.1

6 660

1

10.6

26.7

6

0.4

2

19

1.01 14.5

7

0.9

5

16

1

1.2 16.2

5

11 1.59 0.5 26

1

2178 7.9

1.19 16.3

5

26.6

2

12.6 2.47 0.6 8.3

7

2

7.2 0.48 0.5

2

2805 12.3

0.36

7

12.3

18

5 555 848

0.16 22.4

2

1441 25 2.1 1

3 799

1.6

3 2587

0.9 14.4

2

1946

3 1.2 14.5

6

16

0.6

5

713 9.4 0.6

3

5.2

1

7.7 2.1

7

1 17.1

5

27.9 1.7 0.68

5

5.8

1.08

7

6 129 194

1.48 0.35 16.3

2

3

11.4 1.8

12

6

17

2

2.13

13.4

4 2300 885

0.32 17

5

1

17.4

5 980

20.5

7

18 2.7 1 13

6

14.7 1.8 0.3

7

11.5

1

1.75

6

2.39

14.2

7

0.24 23

6

0.4 17

7

9.5

1.1

2

0.79

5 1172 1726 7.5

0.16 29

7 6064

0.8

6

17

7

12.6

19.8

7

9.6

17.2

5

1.04

4 1819 972 9.2

2

4.8

0.35 20.5

4 13219

27.2

2 2187

14

6 601 1252 7.8 1.57 1 17

Company Type Total Revenues Total Assets Return on Equity Earnings per Share Dividends per Share Average P/E Ratio
AFLAC 7251 29454 1

7.1 2.08 0.2 1

1.5
Albertson’s 14690 5219 2

1.4 0.6
Allstate 20106 80918 20.1 3.56 0.3 10.6
Amerada Hess 8340 7935 0.08 69

8.3
American General 3362 80620 2.1 2

1.2
American Stores 19139 8536 12.2 1.01 0.34 23.5
Amoco 36287 32489 16.7 2.7 1

6.1
Arco Chemical 3995 4116 6.2 1.1 2.8 4

0.4
Ashland 14319 7777 9.5 3.8 1

2.4
Atlantic Richfield 19272 2

1.8 5.41 2.83
Bausch & Lomb 2773 0.8 1.04 2.6
Baxter International 6138 8707 11.5 1.06 1.13 4

7.2
Bristol-Myers Squibb 16701 14977 44.4 3.14 1.52 24.1
Burlington Coat 1777 12.3 1.18 0.02 12.9
Central Maine Power 0.16 0.9 7

9.6
Chevron 41950 35473 18.6 4.95 2.28 1

5.2
CIGNA 14935 108199 13.7 4.8 11.4
Cinergy 4353 8858 13.3 1.59 22.4
Dayton Hudson 27757 14191 1.7 0.33 16.2
Dillard’s 6817 5592 9.2 2.31 15.7
Dominion Resources 7678 20193 7.9 2.15 2.58 1

7.7
Dow Chemical 20018 24040 23.6 3.24 1

1.6
DPL 1356 3585 13.9 0.91 14.3
E. I. DuPont DeNemours 46653 42942 2

1.3 1.23 27.9
Eastman Chemical 4678 5778 16.3 3.63 1.76
Edison International 9235 25101 1.73 13.6
Engelhard 3631 2586 0.38 61.8
Entergy 9562 27001 4.2 1.03 25.4
Equitable 9666 151438 2.86 13.4
Ethyl 53.6 0.71 0.5 12.6
Exxon 137242 9

6064 1

9.4 3.37 1.63 17.1
FPL Group 6369 12449 3.57 1.92 14.4
The GAP 6508 3338 33.7
Georgia Gulf 2.39 0.32 11.8
GIANT Food 4231 1522 0.78 2

6.9
A & P 2995 1.66 0.35 1

7.8
Great Lakes Chemicals 1311 2270 5.5 1.19 0.62 40.5
Green Mountain Power Company 1.57 1.61
Hannaford Bros. 9.9 0.54 26.6
Hercules 1866 2411 3.18 14.5
Houston Industries 6873 18415
Jefferson-Pilot 23131 3.47
Johnson & Johnson 22629 21453 26.7 2.41 0.85
Liberty 3185 11.1 3.34 0.77 12.7
The Limited 9189 4301 0.79 0.48
Lincoln National 4899 77175 0.21 1.96 300.2
Lubrizol 1674 1462 2.66
Lyondell Petrochemical 3010 1559 46.2 3.58 6.4
Mallinkrodt 1868 2988 14.8 2.47 0.66
May Department Stores 12685 9930 20.5 3.11
McKesson 20857 5608
Mercantile Stores 3144 3.53
Merck 23637 25812 36.6 3.74 1.69
Millennium Chemicals 3048 4326
Mobil 65906 43559 16.8 4.01 2.12 17.2
Monsanto 7514 10774 90.7
Morton 2388 1.48 25.2
Murphy Oil 2138 2238 2.94 1.35
Mylan Laboratories 13.5 0.82
NALCO Chemical 1434 18.3
Nevada Power 2339 10.1 1.65 14.2
NIPSCO 4937 14.1 1.53
Olin 2410 17.4
Orion Capital 1591 3884 4.15 9.8
Owens & Minor 3117 0.18 21.7
Pacific Corporation 6278 13880 0.68 1.08 34.2
J. C. Penney 30546 23493 2.13 26.9
Pennzoil 2654 4406 1

5.8 3.76
Pfizer 12504 15336 35.4
Pharmacia & Upjohn 6710 10380 0.61 56.2
Phillips Petroleum 15424 13860 19.9 3.61 1.34 12.4
Poe & Brown 25.1
PPG 7379 6868 28.5 3.94 1.33 14.7
PP&L Resources 3049 9485 1.67
Progressive 4190 7560 18.7 5.31 0.24
Rohm & Haas 3999 3900 19.8 0.63
Ruddick 12.5 1.02
Schering-Plough 6778 6507 51.2 1.95 0.74 24.6
Sears, Roebuck 41296 38700 20.3 2.99 0.92
Stryker 985 1.28 0.11 27.2
Sun 10531 4667
Sunamerica 2114 35637 19.5
Texaco 46667 29600 20.9 4.87 1.75
The TJX Companies 7389 2610 26.3 0.09 8.2
Torchmark 2283 10967 1

7.5 0.59
Tosco 13282 5975 10.9 1.37
Travelers 37609 386555 14.9 2.54
Ultramar Diamond Shamrock 10882 5595 1.94 16.1
Union Carbide 6502 6964 28.8 4.53 10.7
United States Surgical Corporation 1.21
UNOCAL 7530 28.9 2.65 15.5
UNUM 4077 13200 15.2 2.59 0.56
USX-Marathon 15754 10565 1.58 0.76
Valero Energy 5756 2493 2.03 0.42
Warner-Lambert 8180 8031 30.7 0.51 35.7
WEIS Markets 1.87 0.94 16.9
Wellman 1083 1319 0.97
Winn-Dixie Stores 2921 15.3 1.36 0.98
WITCO 2298 1.55 1.12 24.9
Zenith Nation Insurance

Title

ABC/

1

23 Version X

1

1

Week 6 Options

QNT/561 Version 9

University of Phoenix Material

Option 1: Manufacturing Database

This database contains six variables taken from 20 industries and 140 subindustries in the United States. Some of the industries are food products, textile mill products, furniture, chemicals, rubber products, primary metals, industrial machinery, and transportation equipment. The six variables are Number of Employees, Number of Production Workers, Value Added by Manufacture, Cost of Materials, End-of-Year Inventories, and Industry Group. Two variables, Number of Employees and Number of Production Workers, are in units of 1000. Three variables, Value Added by Manufacture, Cost of Materials, and End-of-Year Inventories, are in million-dollar units. The Industry Group variable consists of numbers from 1 to 20 to denote the industry group to which the particular subindustry belongs.

Option 2: Hospital Database

This database contains observations for six variables on U.S. hospitals. These variables include Geographic Region, Control, Service, Census, Number of Births, and Personnel.

The region variable is coded from 1 to 7, and the numbers represent the following regions:

1 = South

2 = Northeast

3 = Midwest

4 = Southwest

5 = Rocky Mountain

6 = California

7 = Northwest

Control is a type of ownership. Four categories of control are included in the database:

1 = government, nonfederal

2 = nongovernment, not-for-profit

3 = for-profit

4 = federal government

Service is the type of hospital. The two types of hospitals used in this database are:

1 = general medical

2 = psychiatric

Option 3: Consumer Food

The consumer food database contains five variables: Annual Food Spending per Household, Annual Household Income, Non-Mortgage Household Debt, Geographic Region of the U.S. of the Household, and Household Location. There are 200 entries for each variable in this database representing 200 different households from various regions and locations in the United States. Annual Food Spending per Household, Annual Household Income, and Non-Mortgage Household Debt are all given in dollars. The variable Region tells in which one of four regions the household resides. In this variable, the Northeast is coded as 1, the Midwest is coded 2, the South is coded as 3, and the West is coded as 4. The variable Location is coded as 1 if the household is in a metropolitan area and 2 if the household is outside a metro area. The data in this database were randomly derived and developed based on actual national norms.

Option 4: Financial Database

The financial database contains observations on seven variables for 100 companies. The variables are Type of Industry, Total Revenues ($ millions), Total Assets ($ millions), Return on Equity (%), Earnings per Share ($), Dividends per Share ($), and Average Price per Earnings (P/E) ratio. The companies represent seven different types of industries. The variable Type displays a company’s industry type as:

1 = apparel

2 = chemical

3 = electric power

4 = grocery

5 = healthcare products

6 = insurance

7 = petroleum

Copyright © XXXX by University of Phoenix. All rights reserved.

Copyright © 2017 by University of Phoenix. All rights reserved.

Title

ABC/

1

23 Version X

1

1

Week 6 Options

QNT/561 Version 9

University of Phoenix Material

Option 1: Manufacturing Database

This database contains six variables taken from 20 industries and 140 subindustries in the United States. Some of the industries are food products, textile mill products, furniture, chemicals, rubber products, primary metals, industrial machinery, and transportation equipment. The six variables are Number of Employees, Number of Production Workers, Value Added by Manufacture, Cost of Materials, End-of-Year Inventories, and Industry Group. Two variables, Number of Employees and Number of Production Workers, are in units of 1000. Three variables, Value Added by Manufacture, Cost of Materials, and End-of-Year Inventories, are in million-dollar units. The Industry Group variable consists of numbers from 1 to 20 to denote the industry group to which the particular subindustry belongs.

Option 2: Hospital Database

This database contains observations for six variables on U.S. hospitals. These variables include Geographic Region, Control, Service, Census, Number of Births, and Personnel.

The region variable is coded from 1 to 7, and the numbers represent the following regions:

1 = South

2 = Northeast

3 = Midwest

4 = Southwest

5 = Rocky Mountain

6 = California

7 = Northwest

Control is a type of ownership. Four categories of control are included in the database:

1 = government, nonfederal

2 = nongovernment, not-for-profit

3 = for-profit

4 = federal government

Service is the type of hospital. The two types of hospitals used in this database are:

1 = general medical

2 = psychiatric

Option 3: Consumer Food

The consumer food database contains five variables: Annual Food Spending per Household, Annual Household Income, Non-Mortgage Household Debt, Geographic Region of the U.S. of the Household, and Household Location. There are 200 entries for each variable in this database representing 200 different households from various regions and locations in the United States. Annual Food Spending per Household, Annual Household Income, and Non-Mortgage Household Debt are all given in dollars. The variable Region tells in which one of four regions the household resides. In this variable, the Northeast is coded as 1, the Midwest is coded 2, the South is coded as 3, and the West is coded as 4. The variable Location is coded as 1 if the household is in a metropolitan area and 2 if the household is outside a metro area. The data in this database were randomly derived and developed based on actual national norms.

Option 4: Financial Database

The financial database contains observations on seven variables for 100 companies. The variables are Type of Industry, Total Revenues ($ millions), Total Assets ($ millions), Return on Equity (%), Earnings per Share ($), Dividends per Share ($), and Average Price per Earnings (P/E) ratio. The companies represent seven different types of industries. The variable Type displays a company’s industry type as:

1 = apparel

2 = chemical

3 = electric power

4 = grocery

5 = healthcare products

6 = insurance

7 = petroleum

Copyright © XXXX by University of Phoenix. All rights reserved.

Copyright © 2017 by University of Phoenix. All rights reserved.

Title

ABC/

1

2

3 Version X

1

Part 3 Inferential Statistics

QNT/561 Version 9

2

Part 3: Inferential Statistics

Option 1: Manufacturing Database

1. The National Association of Manufacturers (NAM) contracts with your consulting company to determine the estimate of mean number of production workers. Construct a 95% confidence interval for the population mean number of production workers. What is the point estimate? How much is the margin of error in the estimate?

2. Suppose the average number of employees per industry group in the manufacturing database is believed to be less than 150 (1000s). Test this belief as the alternative hypothesis by using the 140 SIC Code industries given in the database as the sample. Let α = .10. Assume that the number of employees per industry group are normally distributed in the population.

3. You are also required to determine whether there is a significant difference between mean Value Added by the Manufacturer and the mean Cost of Materials in manufacturing using alpha of 0.01.

4. You are requested to determine whether there is a significantly greater variance among values of Cost of Materials than of End-of-Year Inventories.

Option 2: Hospital Database

1. As a consultant, you need to use the Hospital database and construct a 90% confidence interval to estimate the average census for hospitals. Change the level of confidence to 99%. What happened to the interval? Did the point estimate change?

2. Determine the sample proportion of the Hospital database under the variable “service” that are “general medical” (category 1). From this statistic, construct a 95% confidence interval to estimate the population proportion of hospitals that are “general medical.” What is the point estimate? How much error is there in the interval?

3. Suppose you want to “prove” that the average hospital in the United States averages more than 700 births per year. Use the hospital database as your sample and test this hypothesis. Let alpha be 0.01.

4. On average, do hospitals in the United States employ fewer than 900 personnel? Use the hospital database as your sample and an alpha of 0.10 to test this figure as the alternative hypothesis. Assume that the number of births and number of employees in the hospitals are normally distributed in the population.

Option 3: Consumer Food

1. Suppose you want to test to determine if the average annual food spending for a household in the Midwest region of the U.S. is more than $8,000. Use the Midwest region data and a 1% level of significance to test this hypothesis. Assume that annual food spending is normally distributed in the population.

2. Test to determine if there is a significant difference between households in a metro area and households outside metro areas in annual food spending. Let α = 0.01.

3. The Consumer Food database contains data on Annual Food Spending, Annual Household Income, and Non-Mortgage Household Debt broken down by Region and Location. Using Region as an independent variable with four classification levels (four regions of the U.S.), perform three different one-way ANOVA’s—one for each of the three dependent variables (Annual Food Spending, Annual Household Income, Non-Mortgage Household Debt). Did you find any significant differences by region?

Option 4: Financial Database

1. Use this database as a sample and estimate the earnings per share for all corporations from these data. Select several levels of confidence and compare the results.

2. Are the average earnings per share for companies in the stock market less than $2.50? Use the sample of companies represented by this database to test that hypothesis. Let α = .05.

3. Test to determine whether the average return on equity for all companies is equal to 21. Use this database as the sample and α = .10. Assume that the earnings per share and return on equity are normally distributed in the population.

4. Do various financial indicators differ significantly according to type of company? Use a one-way ANOVA and the financial database to answer this question. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products, Insurance, and Petroleum). Compute three one-way ANOVAs, one for each of the following dependent variables: Earnings Per Share, Dividends Per Share, and Average P/E Ratio.

Copyright © XXXX by University of Phoenix. All rights reserved.

Copyright © 2017 by University of Phoenix. All rights reserved.

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