I have answer file but there used other data, But i need help accordingly attached excel data for Consumer Food

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QNT561_r9_Signature_Assignment_Grading_Guide_week6.zip
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About Your Signature Assignment.docx

About Your Signature Assignment – Due Monday, 20-November

This signature assignment is designed to align with specific program student learning outcome(s) in your program. Program Student Learning Outcomes are broad statements that describe what students should know and be able to do upon completion of their degree. The signature assignments might be graded with an automated rubric that allows the University to collect data that can be aggregated across a location or college/school and used for program improvements.

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. 

Assignment Steps 

Resources: Microsoft Excel®, Signature Assignment Databases, Signature Assignment Options, Part 3: Inferential Statistics

Scenario: Upon successful completion of the MBA program, say 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 1,600-word detailed, statistical report including the following:

· Explain the context of the case

· Provide a research foundation for the topic

· Present graphs

· Explain outliers

· Prepare calculations

· Conduct hypotheses tests

· Discuss inferences you have made from the results 

This assignment is broken down into four parts:

· Part 1 - Preliminary Analysis

· Part 2 - Examination of Descriptive Statistics

· Part 3 - Examination of Inferential Statistics

· Part 4 - Conclusion/Recommendations 

Part 1 - Preliminary Analysis (3-4 paragraphs)

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 (3-4 paragraphs) 

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 (2-3 paragraphs)

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 (1-2 paragraphs)

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. 

Click the Assignment Files tab to submit your assignment.

QNT561_r9_Part_3_Inferential_Statistics_Week_6.doc

Title

ABC/123 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.

QNT561_r9_Signature_Assignment_Databases_Week6.xlsx

Option 1 - Manufacturer

SIC Code No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials End Yr. Inven. Indus. Grp.
201 433 370 23518 78713 3630 1
202 131 83 15724 42774 3157 1
203 204 169 24506 27222 8732 1
204 100 70 21667 37040 3407 1
205 220 137 20712 12030 1155 1
206 89 69 12640 13674 3613 1
207 26 18 4258 19130 1946 1
208 143 72 35210 33521 7199 1
209 171 126 20548 19612 3135 1
211 21 15 23442 5557 5506 2
212 3 2 287 163 42 2
213 2 2 1508 314 155 2
214 6 4 624 2622 554 2
221 52 47 2471 4219 929 3
222 74 63 4307 5357 1427 3
223 13 12 673 1061 325 3
224 17 13 817 707 267 3
225 169 147 8986 10421 2083 3
226 51 41 3145 4140 697 3
227 55 44 4076 7125 1446 3
228 84 76 3806 8994 1014 3
229 61 47 4276 5504 1291 3
231 27 22 1239 716 356 4
232 200 178 9423 8926 2314 4
233 294 250 11045 11121 2727 4
234 38 32 1916 2283 682 4
235 17 14 599 364 197 4
236 34 28 2063 1813 450 4
237 1 1 34 71 17 4
238 31 25 1445 1321 526 4
239 224 179 10603 12376 2747 4
241 83 68 5775 9661 578 5
242 172 147 10404 19285 3979 5
243 257 209 13274 18632 3329 5
244 51 43 1909 2170 355 5
245 82 68 4606 7290 580 5
249 94 78 5518 8135 1604 5
251 273 233 12464 12980 3535 6
252 70 53 5447 4011 829 6
253 37 29 2290 5101 447 6
254 81 61 4182 3755 956 6
259 54 39 2818 2694 718 6
261 15 11 2201 3279 725 7
262 116 90 18848 20596 4257 7
263 55 42 9655 10604 1502 7
265 212 163 15668 24634 3976 7
267 232 182 25918 28963 5427 7
271 403 136 30692 8483 894 8
272 121 16 17982 6940 1216 8
273 136 57 17857 8863 3736 8
274 69 25 9699 2823 874 8
275 604 437 38407 29572 4300 8
276 41 28 3878 3811 688 8
277 21 12 3989 1047 577 8
278 65 50 4388 2055 504 8
279 55 39 4055 1098 236 8
281 80 45 16567 11298 2644 9
282 115 79 25025 34596 6192 9
283 213 106 59813 27187 11533 9
284 126 75 31801 19932 4535 9
285 51 28 8497 9849 2178 9
286 126 75 28886 46935 8577 9
287 37 24 12277 11130 2354 9
289 76 45 11547 13085 2749 9
291 67 43 26006 132880 10718 10
295 25 18 3464 6182 658 10
299 14 8 2187 4446 670 10
301 65 54 7079 7091 1067 11
302 8 7 442 496 175 11
305 61 46 4528 3805 1057 11
306 122 95 7275 7195 1411 11
308 763 598 55621 57264 11874 11
311 15 12 1313 1865 404 12
313 3 2 162 163 35 12
314 37 31 1907 1682 716 12
315 2 2 53 85 62 12
316 6 4 747 395 199 12
317 8 7 328 255 75 12
319 7 6 233 177 40 12
321 12 9 1717 943 282 13
322 60 51 6532 3527 1505 13
323 64 50 4850 4254 883 13
324 17 13 3509 2282 828 13
325 31 25 2176 1387 700 13
326 45 36 2696 1183 600 13
327 205 152 15739 17010 1966 13
328 17 13 999 565 263 13
329 72 53 7838 5432 1652 13
331 221 174 29180 45696 12198 14
332 128 106 9061 6913 1543 14
333 35 26 4200 11184 1834 14
334 15 11 1410 5735 694 14
335 162 123 16670 31892 6377 14
336 94 79 5856 4696 938 14
339 32 23 3164 2790 800 14
341 33 27 3999 9364 1453 15
342 140 107 11750 8720 3124 15
343 45 32 4412 3527 1121 15
344 432 315 27974 31527 7204 15
345 104 81 6936 4909 1768 15
346 259 211 19880 21531 3997 15
347 129 99 7793 6232 1181 15
348 40 24 3528 1689 1077 15
349 300 219 21718 19273 6460 15
351 79 55 10513 12954 3679 16
352 94 70 9545 11858 3339 16
353 205 133 18178 23474 7344 16
354 295 211 22673 14343 6730 16
355 192 110 19221 16515 6823 16
356 265 172 23110 18543 7898 16
357 259 96 41135 60857 10277 16
358 201 147 17521 21819 4857 16
359 392 293 25322 13897 4964 16
361 74 51 6700 5523 1495 17
362 171 120 14278 12657 3887 17
363 108 87 9466 12578 2299 17
364 157 117 13428 11065 3076 17
365 49 37 3459 7621 1070 17
366 258 120 38705 29591 9467 17
367 588 368 84059 44486 13145 17
369 151 106 13920 13398 3514 17
371 772 634 105899 223639 15852 18
372 377 190 45220 42367 36814 18
373 141 108 7903 7760 2165 18
374 31 23 2590 4363 1233 18
375 18 14 1435 1674 412 18
376 81 29 9986 8120 4770 18
379 47 35 3564 5476 1102 18
381 186 68 21071 8760 6183 19
382 272 141 29028 18028 7681 19
384 268 157 31051 16787 7761 19
385 27 17 2390 1020 426 19
386 61 36 14032 8114 2290 19
387 6 4 415 382 177 19
391 43 30 2761 3646 1451 20
393 13 10 685 506 328 20
394 103 76 8327 6604 2608 20
395 35 26 2643 1789 799 20
396 24 19 1406 997 415 20
399 179 123 11199 8530 2861 20

Option 2 - Hospital

Hospital Geog. Region Control Service Census Births Personnel
1 1 2 1 107 312 792
2 1 1 1 198 1077 1762
3 1 2 1 356 1027 2310
4 1 1 1 100 355 328
5 7 1 1 9 168 181
6 4 2 1 159 3810 1077
7 4 4 1 65 735 742
8 4 2 1 48 1 131
9 1 2 1 253 1733 1594
10 1 1 1 21 257 233
11 1 1 1 27 169 241
12 6 3 1 30 430 203
13 6 3 1 43 0 325
14 6 2 1 233 2049 676
15 6 4 1 2 211 347
16 6 1 1 11 16 79
17 6 3 1 84 2648 505
18 6 2 1 219 2450 1543
19 6 3 1 112 1465 755
20 6 3 1 124 0 959
21 6 3 1 50 1993 325
22 6 2 1 142 2275 954
23 6 2 1 111 1494 1091
24 6 1 1 140 1313 671
25 6 3 1 28 451 300
26 6 2 1 154 1689 753
27 6 2 1 150 1583 607
28 6 3 1 144 2017 929
29 6 3 1 42 995 354
30 6 2 1 77 2045 408
31 5 2 1 119 1686 1251
32 5 2 1 27 503 386
33 5 2 1 15 126 144
34 2 2 1 179 2026 2047
35 2 2 1 175 1412 1343
36 2 2 1 461 1517 1723
37 1 3 2 32 0 96
38 1 2 1 74 0 529
39 1 1 1 414 2719 3694
40 1 2 1 253 1074 1042
41 1 3 1 180 1421 1071
42 1 1 1 184 762 1525
43 1 2 1 243 3194 1983
44 1 2 1 115 496 670
45 1 1 1 215 1442 1653
46 1 3 2 48 0 167
47 1 3 1 124 1107 793
48 1 2 1 189 2989 841
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 1064 943
54 1 2 1 154 759 605
55 7 2 1 76 1317 596
56 7 3 1 165 1751 1165
57 3 1 2 295 0 568
58 3 3 1 101 0 507
59 3 2 1 69 714 479
60 3 2 1 12 99 136
61 3 2 1 185 2243 1456
62 3 2 1 378 3966 3486
63 3 2 1 114 1308 885
64 3 3 2 49 0 243
65 3 2 1 106 2514 1001
66 3 2 1 460 3714 3301
67 3 2 1 43 126 337
68 3 4 1 29 556 1193
69 3 2 1 125 1327 1161
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 1217 1224
74 3 2 1 207 2641 1704
75 3 2 1 223 790 815
76 3 2 1 82 520 712
77 3 1 1 64 35 156
78 3 2 1 139 1168 1769
79 3 2 1 109 793 875
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 1618
86 1 1 1 47 0 244
87 1 2 1 80 776 525
88 1 3 1 50 451 472
89 1 3 2 113 0 94
90 1 2 1 45 145 297
91 1 1 1 76 1284 847
92 1 3 1 129 1 234
93 2 2 1 60 319 401
94 2 2 1 418 2154 3928
95 2 2 1 17 295 198
96 2 2 1 138 496 1231
97 2 2 1 64 589 545
98 2 2 1 62 806 663
99 2 1 1 131 701 820
100 2 2 1 265 3968 2581
101 3 4 2 456 0 1298
102 3 2 2 40 0 126
103 3 1 1 310 3655 2534
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 0 864
108 3 3 2 15 0 66
109 3 2 1 78 3063 556
110 3 1 1 123 169 347
111 3 2 1 54 66 239
112 3 2 1 96 827 973
113 1 3 1 82 570 439
114 1 1 2 1106 0 1849
115 1 1 1 30 0 102
116 3 1 2 56 0 262
117 3 4 1 36 342 885
118 3 3 1 127 494 549
119 3 1 2 180 0 611
120 3 4 1 59 0 330
121 5 2 1 127 0 1471
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 1 194 398 575
127 3 2 1 172 1275 1916
128 5 3 1 516 5699 2620
129 5 3 1 120 1364 571
130 5 1 1 179 714 703
131 2 4 1 140 0 535
132 2 3 2 78 0 160
133 2 3 2 68 0 202
134 2 2 1 186 779 1330
135 2 2 1 91 0 370
136 2 1 1 340 2202 3123
137 5 1 1 254 3346 2745
138 5 2 1 108 1071 815
139 5 2 1 61 352 576
140 2 2 1 174 254 502
141 2 1 2 306 0 808
142 2 3 2 28 0 50
143 2 2 1 395 699 728
144 2 2 1 923 2462 4087
145 2 1 1 335 3311 3012
146 1 2 1 46 0 68
147 1 1 1 316 4207 3090
148 1 4 2 416 0 1358
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 1143 2312
153 3 4 2 232 0 1124
154 3 1 2 138 0 336
155 3 2 1 38 509 415
156 3 2 1 245 1026 1779
157 3 1 2 171 0 338
158 3 3 1 51 447 453
159 3 4 1 28 1161 437
160 3 1 2 797 0 261
161 7 2 1 56 922 609
162 7 1 1 69 562 647
163 7 1 1 40 78 61
164 7 4 1 163 0 2074
165 7 2 1 231 2122 2232
166 2 1 2 523 0 948
167 2 4 1 31 0 409
168 2 2 2 43 0 153
169 2 2 1 66 710 741
170 2 2 1 231 1165 1625
171 1 4 1 11 466 538
172 1 3 1 144 1106 789
173 1 3 1 43 376 395
174 3 4 1 185 0 956
175 3 2 1 82 637 362
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 1227 2256
180 1 3 1 93 963 731
181 1 4 1 86 3038 1477
182 1 3 2 28 0 102
183 1 3 2 25 0 106
184 1 3 1 181 868 939
185 5 3 1 39 1189 392
186 5 1 1 302 2849 3516
187 5 2 1 80 1728 785
188 5 2 1 63 2171 607
189 2 2 1 31 364 273
190 2 2 2 170 0 630
191 1 1 1 203 2993 1379
192 1 2 1 296 0 1108
193 1 3 1 83 1964 583
194 7 2 1 84 601 514
195 7 1 1 29 387 216
196 7 2 1 187 1946 1593
197 7 2 1 77 545 1055
198 5 1 2 104 0 399
199 5 1 1 85 838 834
200 5 1 1 47 51 104

Option 3 - Consumer Food

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 1 1
5684 35945 7052 1 1
10706 52687 16149 1 1
14112 74041 21839 1 1
13855 63182 18866 1 1
15619 79064 21899 1 1
2694 25981 8774 1 1
9127 57424 15766 1 1
13514 72045 27685 1 1
6314 38046 8545 1 1
7622 52408 28057 1 1
4322 41405 6998 1 1
3805 29684 4806 1 1
6674 49246 13592 1 1
7347 41491 4088 1 1
2911 26703 15876 1 1
8026 48753 16714 1 1
8567 55555 16783 1 1
10345 71483 21407 1 1
8694 50980 19114 1 1
8821 46403 7817 1 1
8678 51927 14415 1 1
14331 84769 17295 1 1
9619 59062 16687 1 1
9286 57952 14161 1 1
8206 58355 19538 1 1
16408 81694 15187 1 1
12757 69522 14651 1 1
17740 96132 0 1 1
7739 57796 22057 1 1
15383 88276 1896 1 1
4579 32264 7979 1 1
11679 65928 0 1 1
12877 69924 27330 1 1
16232 91108 9876 1 1
9621 54070 19908 1 1
8171 47238 17819 1 1
12128 77427 31340 1 1
8642 59805 4963 1 1
12400 60334 6632 1 1
9185 54114 18593 1 2
7862 40680 15202 1 2
9775 58263 1486 1 2
6771 52008 21713 1 2
3059 39643 12179 1 2
13211 70309 13221 1 2
7408 46450 5602 1 2
11581 76140 33874 1 2
14233 80833 11478 1 2
3352 31899 2762 1 2
2630 21647 2663 1 2
9093 65924 11355 1 2
12652 65923 5132 1 2
9559 62811 12613 1 2
6112 42335 3149 1 2
10431 65134 15196 1 2
12630 64621 21433 1 2
4578 36553 5502 1 2
9551 62910 11376 1 2
10262 70727 13287 1 2
9551 57634 11857 2 1
10143 56549 16136 2 1
8955 59662 11627 2 1
10197 57350 18432 2 1
11234 56447 10871 2 1
9320 61136 0 2 1
9089 51526 4902 2 1
12300 79979 17270 2 1
11484 66733 15145 2 1
11215 75359 15611 2 1
7204 40795 8975 2 1
5579 39128 6576 2 1
11723 75482 12508 2 1
9353 63998 0 2 1
7761 45845 6671 2 1
4261 38223 8576 2 1
9830 66787 1178 2 1
12386 77852 936 2 1
8673 55825 14167 2 1
10944 57022 9018 2 1
9910 64263 12768 2 1
9928 75881 17423 2 1
4264 34343 21323 2 1
7971 41243 21009 2 1
8290 53021 20151 2 1
12669 66991 9250 2 1
7272 49719 20838 2 1
9784 58399 16065 2 1
9187 50477 9407 2 1
5866 39112 20409 2 1
9456 51886 11668 2 2
6270 34797 146 2 2
9518 62348 5201 2 2
10968 78704 17002 2 2
8865 53620 32004 2 2
9226 51577 15922 2 2
4913 34761 17704 2 2
6976 60968 17799 2 2
8152 51281 8167 2 2
2887 25013 18763 2 2
8062 59238 10815 2 2
8895 47344 11814 2 2
8444 52645 22469 2 2
6148 35309 17139 2 2
4563 34355 10612 2 2
8185 50630 21187 3 1
3391 29056 15735 3 1
7436 48721 18363 3 1
9522 50459 16478 3 1
11290 72805 21238 3 1
10403 56954 22218 3 1
4693 39343 24696 3 1
5626 38833 14371 3 1
11869 55021 35576 3 1
13055 77605 817 3 1
8783 57937 18591 3 1
13031 63343 25531 3 1
3681 36479 17950 3 1
5549 40381 14257 3 1
4108 26309 26581 3 1
6314 41421 22470 3 1
7700 54579 29065 3 1
7479 40551 31757 3 1
9093 50369 6404 3 1
9863 54422 24334 3 1
8043 51836 26213 3 2
9552 73600 36374 3 2
9286 51873 29631 3 2
7987 48003 17261 3 2
3875 36519 13579 3 2
10746 75152 10659 3 2
6888 44974 23711 3 2
5479 48923 4594 3 2
6949 43769 21221 3 2
10650 75947 33357 3 2
5188 41423 33641 3 2
5311 40189 17791 3 2
4691 36772 5829 3 2
8056 59690 19594 3 2
11304 53654 23066 3 2
8112 59067 240 3 2
8696 65962 0 3 2
5869 37254 10157 3 2
3776 33568 14143 3 2
11829 56934 0 3 2
13087 88822 17565 4 1
10986 59635 27863 4 1
5762 38407 18867 4 1
11617 78627 11894 4 1
9895 47710 22930 4 1
16293 64443 31687 4 1
8185 58871 35424 4 1
13972 87954 11549 4 1
11243 54778 12552 4 1
4635 39825 19494 4 1
10063 49536 12195 4 1
8426 60102 13787 4 1
7436 49139 22356 4 1
11747 51052 4553 4 1
15397 70500 12025 4 1
6842 54894 16217 4 1
9678 60570 4106 4 1
12852 57625 31228 4 1
10114 56956 25907 4 1
8496 61400 1093 4 1
6689 50532 17106 4 1
15696 72774 17793 4 1
9841 69981 21607 4 1
12529 66891 17689 4 1
10210 67431 19995 4 1
8868 64782 14489 4 1
6426 38987 17864 4 1
11096 64867 5839 4 1
10086 50421 8689 4 1
2587 27076 17534 4 1
12492 51784 20284 4 2
8456 54135 22037 4 2
6801 53291 23342 4 2
6339 49804 34943 4 2
7802 52205 28579 4 2
9717 72841 22349 4 2
6026 46238 20165 4 2
5618 45938 10538 4 2
10217 77716 18516 4 2
8338 59711 7980 4 2
9048 42106 19786 4 2
4017 36462 9935 4 2
10906 53403 18177 4 2
15148 71290 6696 4 2
8830 66759 20972 4 2
8481 57616 28767 4 2
11358 76221 1373 4 2
10553 78202 5920 4 2
6969 55164 24795 4 2
13219 61171 21482 4 2
3543 34093 25969 4 2
7326 50647 10750 4 2
8458 59898 22940 4 2
11766 52884 25970 4 2
9908 73629 7112 4 2

Option 4 - Financial

Company Type Total Revenues Total Assets Return on Equity Earnings per Share Dividends per Share Average P/E Ratio
AFLAC 6 7251 29454 17.1 2.08 0.22 11.5
Albertson's 4 14690 5219 21.4 2.08 0.63 19
Allstate 6 20106 80918 20.1 3.56 0.36 10.6
Amerada Hess 7 8340 7935 0.2 0.08 0.6 698.3
American General 6 3362 80620 7.1 2.19 1.4 21.2
American Stores 4 19139 8536 12.2 1.01 0.34 23.5
Amoco 7 36287 32489 16.7 2.76 1.4 16.1
Arco Chemical 2 3995 4116 6.2 1.14 2.8 40.4
Ashland 7 14319 7777 9.5 3.8 1.1 12.4
Atlantic Richfield 7 19272 25322 21.8 5.41 2.83 3.8
Bausch & Lomb 5 1916 2773 6 0.89 1.04 2.6
Baxter International 5 6138 8707 11.5 1.06 1.13 47.2
Bristol-Myers Squibb 5 16701 14977 44.4 3.14 1.52 24.1
Burlington Coat 1 1777 775 12.3 1.18 0.02 12.9
Central Maine Power 3 954 2299 2.4 0.16 0.9 79.6
Chevron 7 41950 35473 18.6 4.95 2.28 15.2
CIGNA 6 14935 108199 13.7 4.88 1.1 11.4
Cinergy 3 4353 8858 13.3 1.59 1.8 22.4
Dayton Hudson 1 27757 14191 18 1.7 0.33 16.2
Dillard's 1 6817 5592 9.2 2.31 0.16 15.7
Dominion Resources 3 7678 20193 7.9 2.15 2.58 17.7
Dow Chemical 2 20018 24040 23.6 7.7 3.24 11.6
DPL 3 1356 3585 13.9 1.2 0.91 14.3
E. I. DuPont DeNemours 2 46653 42942 21.3 2.08 1.23 27.9
Eastman Chemical 2 4678 5778 16.3 3.63 1.76 16
Edison International 3 9235 25101 12.3 1.73 1 13.6
Engelhard 2 3631 2586 6.1 0.33 0.38 61.8
Entergy 3 9562 27001 4.2 1.03 1.8 25.4
Equitable 6 9666 151438 12.3 2.86 0.2 13.4
Ethyl 7 1064 1067 53.6 0.71 0.5 12.6
Exxon 7 137242 96064 19.4 3.37 1.63 17.1
FPL Group 3 6369 12449 12.2 3.57 1.92 14.4
The GAP 1 6508 3338 33.7 1.3 0.2 22
Georgia Gulf 2 966 613 228 2.39 0.32 11.8
GIANT Food 4 4231 1522 7.9 1.18 0.78 26.9
A & P 4 10262 2995 6.9 1.66 0.35 17.8
Great Lakes Chemicals 2 1311 2270 5.5 1.19 0.62 40.5
Green Mountain Power Company 3 179 326 8.3 1.57 1.61 14
Hannaford Bros. 4 3226 1227 9.9 1.4 0.54 26.6
Hercules 2 1866 2411 47 3.18 1 14.5
Houston Industries 3 6873 18415 8 1.66 1.5 13.7
Jefferson-Pilot 6 2578 23131 14.5 3.47 1.04 13.3
Johnson & Johnson 5 22629 21453 26.7 2.41 0.85 24.1
Liberty 6 660 3185 11.1 3.34 0.77 12.7
The Limited 1 9189 4301 10.6 0.79 0.48 26.7
Lincoln National 6 4899 77175 0.4 0.21 1.96 300.2
Lubrizol 2 1674 1462 19 2.66 1.01 14.5
Lyondell Petrochemical 7 3010 1559 46.2 3.58 0.9 6.4
Mallinkrodt 5 1868 2988 14.8 2.47 0.66 16
May Department Stores 1 12685 9930 20.5 3.11 1.2 16.2
McKesson 5 20857 5608 11 1.59 0.5 26
Mercantile Stores 1 3144 2178 7.9 3.53 1.19 16.3
Merck 5 23637 25812 36.6 3.74 1.69 26.6
Millennium Chemicals 2 3048 4326 12.6 2.47 0.6 8.3
Mobil 7 65906 43559 16.8 4.01 2.12 17.2
Monsanto 2 7514 10774 7.2 0.48 0.5 90.7
Morton 2 2388 2805 12.3 1.48 0.36 25.2
Murphy Oil 7 2138 2238 12.3 2.94 1.35 18
Mylan Laboratories 5 555 848 13.5 0.82 0.16 22.4
NALCO Chemical 2 1434 1441 25 2.1 1 18.3
Nevada Power 3 799 2339 10.1 1.65 1.6 14.2
NIPSCO 3 2587 4937 14.1 1.53 0.9 14.4
Olin 2 2410 1946 17.4 3 1.2 14.5
Orion Capital 6 1591 3884 16 4.15 0.6 9.8
Owens & Minor 5 3117 713 9.4 0.6 0.18 21.7
Pacific Corporation 3 6278 13880 5.2 0.68 1.08 34.2
J. C. Penney 1 30546 23493 7.7 2.1 2.13 26.9
Pennzoil 7 2654 4406 15.8 3.76 1 17.1
Pfizer 5 12504 15336 27.9 1.7 0.68 35.4
Pharmacia & Upjohn 5 6710 10380 5.8 0.61 1.08 56.2
Phillips Petroleum 7 15424 13860 19.9 3.61 1.34 12.4
Poe & Brown 6 129 194 25.1 1.48 0.35 16.3
PPG 2 7379 6868 28.5 3.94 1.33 14.7
PP&L Resources 3 3049 9485 11.4 1.8 1.67 12
Progressive 6 4190 7560 18.7 5.31 0.24 17
Rohm & Haas 2 3999 3900 19.8 2.13 0.63 13.4
Ruddick 4 2300 885 12.5 1.02 0.32 17
Schering-Plough 5 6778 6507 51.2 1.95 0.74 24.6
Sears, Roebuck 1 41296 38700 20.3 2.99 0.92 17.4
Stryker 5 980 985 20.5 1.28 0.11 27.2
Sun 7 10531 4667 18 2.7 1 13
Sunamerica 6 2114 35637 14.7 1.8 0.3 19.5
Texaco 7 46667 29600 20.9 4.87 1.75 11.5
The TJX Companies 1 7389 2610 26.3 1.75 0.09 8.2
Torchmark 6 2283 10967 17.5 2.39 0.59 14.2
Tosco 7 13282 5975 10.9 1.37 0.24 23
Travelers 6 37609 386555 14.9 2.54 0.4 17
Ultramar Diamond Shamrock 7 10882 5595 9.5 1.94 1.1 16.1
Union Carbide 2 6502 6964 28.8 4.53 0.79 10.7
United States Surgical Corporation 5 1172 1726 7.5 1.21 0.16 29
UNOCAL 7 6064 7530 28.9 2.65 0.8 15.5
UNUM 6 4077 13200 15.2 2.59 0.56 17
USX-Marathon 7 15754 10565 12.6 1.58 0.76 19.8
Valero Energy 7 5756 2493 9.6 2.03 0.42 17.2
Warner-Lambert 5 8180 8031 30.7 1.04 0.51 35.7
WEIS Markets 4 1819 972 9.2 1.87 0.94 16.9
Wellman 2 1083 1319 4.8 0.97 0.35 20.5
Winn-Dixie Stores 4 13219 2921 15.3 1.36 0.98 27.2
WITCO 2 2187 2298 14 1.55 1.12 24.9
Zenith Nation Insurance 6 601 1252 7.8 1.57 1 17

QNT561_r9_Signature_Assignment_Grading_Guide_week6.doc

Signature Assignment

Grading Guide

QNT/561 Version 9

2

image1.png

Signature Assignment Grading Guide

QNT/561 Version 9

Applied Business Research and Statistics

Copyright

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Edited in accordance with University of Phoenix® editorial standards and practices.

Individual Assignment: Signature Assignment

Purpose of Assignment

The purpose of this assignment is for students to synthesize the concepts learned throughout the course. Provide students an opportunity to build critical thinking skills, develop businesses and organizations, and solve problems that require data.

Resources Required

· Microsoft Excel®

· Signature Assignment Databases

· Signature Assignment Options

· Part 3: Inferential Statistics

Grading Guide

Content

Met

Partially Met

Not Met

Comments:

Scenario: Upon successful completion of the MBA program, say 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 1,600-word detailed, statistical report including the following:

· Explain the context of the case

· Provide a research foundation for the topic

· Present graphs

· Explain outliers

· Prepare calculations

· Conduct hypotheses tests

· Discuss inferences you have made from the results

This assignment is broken down into four parts:

· Part 1 - Preliminary Analysis

· Part 2 - Examination of Descriptive Statistics

· Part 3 - Examination of Inferential Statistics

· Part 4 - Conclusion/Recommendations

Part 1 – Preliminary Analysis (3 – 4 paragraphs)

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?

· Clearly and in sufficient detail, describe the population in the study.

· 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 (3 – 4 paragraphs)

· 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 (2 – 3 paragraphs)

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 (1 – 2 paragraphs)

· 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?

Total Available

Total Earned

13

#/13

Writing Guidelines

Met

Partially Met

Not Met

Comments:

The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements.

Intellectual property is recognized with in-text citations and a reference page.

Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper.

Sentences are complete, clear, and concise.

Rules of grammar and usage are followed including spelling and punctuation.

Total Available

Total Earned

 

3

#/3

Assignment Total

#

16

#/16

Additional comments: