Week 6 Assignment

User Generated

Oyvmmneq64

Mathematics

Description

About Your Signature Assignment

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 the following databases:

  • Consumer Food

Select one of the databases based on the information in the Signature Assignment Options. (which has been selected)

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.

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.

Unformatted Attachment Preview

Part 3 Inferential Statistics QNT/561 Version 9 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 Copyright © 2017 by University of Phoenix. All rights reserved. 1 Part 3 Inferential Statistics QNT/561 Version 9 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 © 2017 by University of Phoenix. All rights reserved. 2 SIC Code No. Emp. No. Prod. Wkrs. Value Added by Mfg. Cost of Materials End Yr. Inven. 201 433 370 23518 78713 3630 202 131 83 15724 42774 3157 203 204 169 24506 27222 8732 204 100 70 21667 37040 3407 205 220 137 20712 12030 1155 206 89 69 12640 13674 3613 207 26 18 4258 19130 1946 208 143 72 35210 33521 7199 209 171 126 20548 19612 3135 211 21 15 23442 5557 5506 212 3 2 287 163 42 213 2 2 1508 314 155 214 6 4 624 2622 554 221 52 47 2471 4219 929 222 74 63 4307 5357 1427 223 13 12 673 1061 325 224 17 13 817 707 267 225 169 147 8986 10421 2083 226 51 41 3145 4140 697 227 55 44 4076 7125 1446 228 84 76 3806 8994 1014 229 61 47 4276 5504 1291 231 27 22 1239 716 356 232 200 178 9423 8926 2314 233 294 250 11045 11121 2727 234 38 32 1916 2283 682 235 17 14 599 364 197 236 34 28 2063 1813 450 237 1 1 34 71 17 238 31 25 1445 1321 526 239 224 179 10603 12376 2747 241 83 68 5775 9661 578 242 172 147 10404 19285 3979 243 257 209 13274 18632 3329 244 51 43 1909 2170 355 245 82 68 4606 7290 580 249 94 78 5518 8135 1604 251 273 233 12464 12980 3535 252 70 53 5447 4011 829 253 37 29 2290 5101 447 254 81 61 4182 3755 956 259 54 39 2818 2694 718 261 15 11 2201 3279 725 262 116 90 18848 20596 4257 263 55 42 9655 10604 1502 265 212 163 15668 24634 3976 267 271 272 273 274 275 276 277 278 279 281 282 283 284 285 286 287 289 291 295 299 301 302 305 306 308 311 313 314 315 316 317 319 321 322 323 324 325 326 327 328 329 331 332 333 334 335 232 403 121 136 69 604 41 21 65 55 80 115 213 126 51 126 37 76 67 25 14 65 8 61 122 763 15 3 37 2 6 8 7 12 60 64 17 31 45 205 17 72 221 128 35 15 162 182 136 16 57 25 437 28 12 50 39 45 79 106 75 28 75 24 45 43 18 8 54 7 46 95 598 12 2 31 2 4 7 6 9 51 50 13 25 36 152 13 53 174 106 26 11 123 25918 30692 17982 17857 9699 38407 3878 3989 4388 4055 16567 25025 59813 31801 8497 28886 12277 11547 26006 3464 2187 7079 442 4528 7275 55621 1313 162 1907 53 747 328 233 1717 6532 4850 3509 2176 2696 15739 999 7838 29180 9061 4200 1410 16670 28963 8483 6940 8863 2823 29572 3811 1047 2055 1098 11298 34596 27187 19932 9849 46935 11130 13085 132880 6182 4446 7091 496 3805 7195 57264 1865 163 1682 85 395 255 177 943 3527 4254 2282 1387 1183 17010 565 5432 45696 6913 11184 5735 31892 5427 894 1216 3736 874 4300 688 577 504 236 2644 6192 11533 4535 2178 8577 2354 2749 10718 658 670 1067 175 1057 1411 11874 404 35 716 62 199 75 40 282 1505 883 828 700 600 1966 263 1652 12198 1543 1834 694 6377 336 339 341 342 343 344 345 346 347 348 349 351 352 353 354 355 356 357 358 359 361 362 363 364 365 366 367 369 371 372 373 374 375 376 379 381 382 384 385 386 387 391 393 394 395 396 399 94 32 33 140 45 432 104 259 129 40 300 79 94 205 295 192 265 259 201 392 74 171 108 157 49 258 588 151 772 377 141 31 18 81 47 186 272 268 27 61 6 43 13 103 35 24 179 79 23 27 107 32 315 81 211 99 24 219 55 70 133 211 110 172 96 147 293 51 120 87 117 37 120 368 106 634 190 108 23 14 29 35 68 141 157 17 36 4 30 10 76 26 19 123 5856 3164 3999 11750 4412 27974 6936 19880 7793 3528 21718 10513 9545 18178 22673 19221 23110 41135 17521 25322 6700 14278 9466 13428 3459 38705 84059 13920 105899 45220 7903 2590 1435 9986 3564 21071 29028 31051 2390 14032 415 2761 685 8327 2643 1406 11199 4696 2790 9364 8720 3527 31527 4909 21531 6232 1689 19273 12954 11858 23474 14343 16515 18543 60857 21819 13897 5523 12657 12578 11065 7621 29591 44486 13398 223639 42367 7760 4363 1674 8120 5476 8760 18028 16787 1020 8114 382 3646 506 6604 1789 997 8530 938 800 1453 3124 1121 7204 1768 3997 1181 1077 6460 3679 3339 7344 6730 6823 7898 10277 4857 4964 1495 3887 2299 3076 1070 9467 13145 3514 15852 36814 2165 1233 412 4770 1102 6183 7681 7761 426 2290 177 1451 328 2608 799 415 2861 Indus. Grp. 1 1 1 1 1 1 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 6 6 6 6 6 7 7 7 7 7 8 8 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 10 10 10 11 11 11 11 11 12 12 12 12 12 12 12 13 13 13 13 13 13 13 13 13 14 14 14 14 14 14 14 15 15 15 15 15 15 15 15 15 16 16 16 16 16 16 16 16 16 17 17 17 17 17 17 17 17 18 18 18 18 18 18 18 19 19 19 19 19 19 20 20 20 20 20 20 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 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 1 1 1 1 1 1 1 1 7 7 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 2 3 2 1 1 3 2 1 2 2 3 1 3 2 2 2 2 2 3 2 2 2 4 2 2 1 3 1 2 2 2 1 2 2 1 3 1 1 3 4 1 2 3 3 2 1 3 2 1 1 1 1 1 1 1 1 1 1 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 1 1 2 2 1 1 1 1 2 1 1 1 1 124 189 181 9 28 288 108 154 76 165 295 101 69 12 185 378 114 49 106 460 43 29 125 17 10 14 173 207 223 82 64 139 109 298 52 34 168 21 390 47 80 50 113 45 76 129 60 1107 2989 113 0 0 173 1064 759 1317 1751 0 0 714 99 2243 3966 1308 0 2514 3714 126 556 1327 415 216 339 1217 2641 790 520 35 1168 793 0 0 14 0 0 0 0 776 451 0 145 1284 1 319 793 841 316 93 373 263 943 605 596 1165 568 507 479 136 1456 3486 885 243 1001 3301 337 1193 1161 322 185 205 1224 1704 815 712 156 1769 875 790 308 70 494 111 1618 244 525 472 94 297 847 234 401 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 3 3 3 3 3 5 5 5 5 3 3 3 5 5 5 2 2 2 2 2 2 5 5 5 2 2 2 2 2 2 1 2 4 2 1 3 3 4 1 3 2 1 2 2 3 1 1 1 4 3 1 4 2 1 4 2 3 1 2 3 3 1 4 3 3 2 2 1 1 2 2 2 1 1 1 1 1 1 1 2 2 1 1 2 1 2 2 1 1 1 1 1 2 1 2 1 1 2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 1 1 1 1 1 1 1 418 17 138 64 62 131 265 456 40 310 72 19 112 375 15 78 123 54 96 82 1106 30 56 36 127 180 59 127 37 13 100 47 194 172 516 120 179 140 78 68 186 91 340 254 108 61 174 2154 295 496 589 806 701 3968 0 0 3655 0 0 0 0 0 3063 169 66 827 570 0 0 0 342 494 0 0 0 0 286 235 339 398 1275 5699 1364 714 0 0 0 779 0 2202 3346 1071 352 254 3928 198 1231 545 663 820 2581 1298 126 2534 251 85 432 864 66 556 347 239 973 439 1849 102 262 885 549 611 330 1471 75 262 328 377 575 1916 2620 571 703 535 160 202 1330 370 3123 2745 815 576 502 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 2 2 2 2 2 1 1 1 1 1 3 3 3 3 3 3 3 3 3 3 7 7 7 7 7 2 2 2 2 2 1 1 1 3 3 1 1 1 1 1 1 1 1 1 5 5 5 1 3 2 2 1 2 1 4 1 2 2 2 4 1 2 2 1 3 4 1 2 1 1 4 2 1 4 2 2 2 4 3 3 4 2 2 3 3 2 3 4 3 3 3 3 1 2 2 2 1 1 1 1 1 2 1 1 1 1 2 2 1 1 2 1 1 2 1 1 1 1 1 2 1 2 1 1 1 1 1 1 1 2 1 1 1 1 1 2 2 1 1 1 1 306 28 395 923 335 46 316 416 74 86 38 147 232 138 38 245 171 51 28 797 56 69 40 163 231 523 31 43 66 231 11 144 43 185 82 49 24 63 274 93 86 28 25 181 39 302 80 0 0 699 2462 3311 0 4207 0 339 130 91 1143 0 0 509 1026 0 447 1161 0 922 562 78 0 2122 0 0 0 710 1165 466 1106 376 0 637 0 352 447 1227 963 3038 0 0 868 1189 2849 1728 808 50 728 4087 3012 68 3090 1358 576 284 145 2312 1124 336 415 1779 338 453 437 261 609 647 61 2074 2232 948 409 153 741 1625 538 789 395 956 362 144 229 396 2256 731 1477 102 106 939 392 3516 785 188 189 190 191 192 193 194 195 196 197 198 199 200 5 2 2 1 1 1 7 7 7 7 5 5 5 2 2 2 1 2 3 2 1 2 2 1 1 1 1 1 2 1 1 1 1 1 1 1 2 1 1 63 31 170 203 296 83 84 29 187 77 104 85 47 2171 364 0 2993 0 1964 601 387 1946 545 0 838 51 607 273 630 1379 1108 583 514 216 1593 1055 399 834 104 Region: 1 Location: Annual Annual Non = NE 2 = 1 = Metro Food Househol mortgage MW 3 = 2= Spending d Income household S 4 = Outside ($) ($) debt ($) W 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 9775 6771 3059 13211 7408 11581 14233 3352 2630 9093 12652 9559 6112 10431 12630 4578 9551 10262 9551 10143 8955 10197 11234 9320 9089 12300 11484 11215 7204 5579 11723 9353 7761 4261 9830 12386 8673 10944 9910 9928 4264 7971 8290 12669 7272 9784 40680 58263 52008 39643 70309 46450 76140 80833 31899 21647 65924 65923 62811 42335 65134 64621 36553 62910 70727 57634 56549 59662 57350 56447 61136 51526 79979 66733 75359 40795 39128 75482 63998 45845 38223 66787 77852 55825 57022 64263 75881 34343 41243 53021 66991 49719 58399 15202 1486 21713 12179 13221 5602 33874 11478 2762 2663 11355 5132 12613 3149 15196 21433 5502 11376 13287 11857 16136 11627 18432 10871 0 4902 17270 15145 15611 8975 6576 12508 0 6671 8576 1178 936 14167 9018 12768 17423 21323 21009 20151 9250 20838 16065 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 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 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 9187 5866 9456 6270 9518 10968 8865 9226 4913 6976 8152 2887 8062 8895 8444 6148 4563 8185 3391 7436 9522 11290 10403 4693 5626 11869 13055 8783 13031 3681 5549 4108 6314 7700 7479 9093 9863 8043 9552 9286 7987 3875 10746 6888 5479 6949 10650 50477 39112 51886 34797 62348 78704 53620 51577 34761 60968 51281 25013 59238 47344 52645 35309 34355 50630 29056 48721 50459 72805 56954 39343 38833 55021 77605 57937 63343 36479 40381 26309 41421 54579 40551 50369 54422 51836 73600 51873 48003 36519 75152 44974 48923 43769 75947 9407 20409 11668 146 5201 17002 32004 15922 17704 17799 8167 18763 10815 11814 22469 17139 10612 21187 15735 18363 16478 21238 22218 24696 14371 35576 817 18591 25531 17950 14257 26581 22470 29065 31757 6404 24334 26213 36374 29631 17261 13579 10659 23711 4594 21221 33357 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 5188 5311 4691 8056 11304 8112 8696 5869 3776 11829 13087 10986 5762 11617 9895 16293 8185 13972 11243 4635 10063 8426 7436 11747 15397 6842 9678 12852 10114 8496 6689 15696 9841 12529 10210 8868 6426 11096 10086 2587 12492 8456 6801 6339 7802 9717 6026 41423 40189 36772 59690 53654 59067 65962 37254 33568 56934 88822 59635 38407 78627 47710 64443 58871 87954 54778 39825 49536 60102 49139 51052 70500 54894 60570 57625 56956 61400 50532 72774 69981 66891 67431 64782 38987 64867 50421 27076 51784 54135 53291 49804 52205 72841 46238 33641 17791 5829 19594 23066 240 0 10157 14143 0 17565 27863 18867 11894 22930 31687 35424 11549 12552 19494 12195 13787 22356 4553 12025 16217 4106 31228 25907 1093 17106 17793 21607 17689 19995 14489 17864 5839 8689 17534 20284 22037 23342 34943 28579 22349 20165 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 5618 10217 8338 9048 4017 10906 15148 8830 8481 11358 10553 6969 13219 3543 7326 8458 11766 9908 45938 77716 59711 42106 36462 53403 71290 66759 57616 76221 78202 55164 61171 34093 50647 59898 52884 73629 10538 18516 7980 19786 9935 18177 6696 20972 28767 1373 5920 24795 21482 25969 10750 22940 25970 7112 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 Company Type AFLAC Albertson's Allstate Amerada Hess American General American Stores Amoco Arco Chemical Ashland Atlantic Richfield Bausch & Lomb Baxter International Bristol-Myers Squibb Burlington Coat Central Maine Power Chevron CIGNA Cinergy Dayton Hudson Dillard's Dominion Resources Dow Chemical DPL E. I. DuPont DeNemours Eastman Chemical Edison International Engelhard Entergy Equitable Ethyl Exxon FPL Group The GAP Georgia Gulf GIANT Food A&P Great Lakes Chemicals Green Mountain Power Company Hannaford Bros. Hercules Houston Industries Jefferson-Pilot Johnson & Johnson Liberty The Limited Lincoln National 6 4 6 7 6 4 7 2 7 7 5 5 5 1 3 7 6 3 1 1 3 2 3 2 2 3 2 3 6 7 7 3 1 2 4 4 2 3 4 2 3 6 5 6 1 6 Total Revenues Total Assets Return on Equity 7251 29454 17,1 14690 5219 21,4 20106 80918 20,1 8340 7935 0,2 3362 80620 7,1 19139 8536 12,2 36287 32489 16,7 3995 4116 6,2 14319 7777 9,5 19272 25322 21,8 1916 2773 6 6138 8707 11,5 16701 14977 44,4 1777 775 12,3 954 2299 2,4 41950 35473 18,6 14935 108199 13,7 4353 8858 13,3 27757 14191 18 6817 5592 9,2 7678 20193 7,9 20018 24040 23,6 1356 3585 13,9 46653 42942 21,3 4678 5778 16,3 9235 25101 12,3 3631 2586 6,1 9562 27001 4,2 9666 151438 12,3 1064 1067 53,6 137242 96064 19,4 6369 12449 12,2 6508 3338 33,7 966 613 228 4231 1522 7,9 10262 2995 6,9 1311 2270 5,5 179 326 8,3 3226 1227 9,9 1866 2411 47 6873 18415 8 2578 23131 14,5 22629 21453 26,7 660 3185 11,1 9189 4301 10,6 4899 77175 0,4 Lubrizol Lyondell Petrochemical Mallinkrodt May Department Stores McKesson Mercantile Stores Merck Millennium Chemicals Mobil Monsanto Morton Murphy Oil Mylan Laboratories NALCO Chemical Nevada Power NIPSCO Olin Orion Capital Owens & Minor Pacific Corporation J. C. Penney Pennzoil Pfizer Pharmacia & Upjohn Phillips Petroleum Poe & Brown PPG PP&L Resources Progressive Rohm & Haas Ruddick Schering-Plough Sears, Roebuck Stryker Sun Sunamerica Texaco The TJX Companies Torchmark Tosco Travelers Ultramar Diamond Shamrock Union Carbide United States Surgical Corporation UNOCAL UNUM USX-Marathon 2 7 5 1 5 1 5 2 7 2 2 7 5 2 3 3 2 6 5 3 1 7 5 5 7 6 2 3 6 2 4 5 1 5 7 6 7 1 6 7 6 7 2 5 7 6 7 1674 3010 1868 12685 20857 3144 23637 3048 65906 7514 2388 2138 555 1434 799 2587 2410 1591 3117 6278 30546 2654 12504 6710 15424 129 7379 3049 4190 3999 2300 6778 41296 980 10531 2114 46667 7389 2283 13282 37609 10882 6502 1172 6064 4077 15754 1462 1559 2988 9930 5608 2178 25812 4326 43559 10774 2805 2238 848 1441 2339 4937 1946 3884 713 13880 23493 4406 15336 10380 13860 194 6868 9485 7560 3900 885 6507 38700 985 4667 35637 29600 2610 10967 5975 386555 5595 6964 1726 7530 13200 10565 19 46,2 14,8 20,5 11 7,9 36,6 12,6 16,8 7,2 12,3 12,3 13,5 25 10,1 14,1 17,4 16 9,4 5,2 7,7 15,8 27,9 5,8 19,9 25,1 28,5 11,4 18,7 19,8 12,5 51,2 20,3 20,5 18 14,7 20,9 26,3 17,5 10,9 14,9 9,5 28,8 7,5 28,9 15,2 12,6 Valero Energy Warner-Lambert WEIS Markets Wellman Winn-Dixie Stores WITCO Zenith Nation Insurance 7 5 4 2 4 2 6 5756 8180 1819 1083 13219 2187 601 2493 8031 972 1319 2921 2298 1252 9,6 30,7 9,2 4,8 15,3 14 7,8 Earnings per Share Dividends per Share 2,08 2,08 3,56 0,08 2,19 1,01 2,76 1,14 3,8 5,41 0,89 1,06 3,14 1,18 0,16 4,95 4,88 1,59 1,7 2,31 2,15 7,7 1,2 2,08 3,63 1,73 0,33 1,03 2,86 0,71 3,37 3,57 1,3 2,39 1,18 1,66 1,19 1,57 1,4 3,18 1,66 3,47 2,41 3,34 0,79 0,21 Average P/E Ratio 0,22 0,63 0,36 0,6 1,4 0,34 1,4 2,8 1,1 2,83 1,04 1,13 1,52 0,02 0,9 2,28 1,1 1,8 0,33 0,16 2,58 3,24 0,91 1,23 1,76 1 0,38 1,8 0,2 0,5 1,63 1,92 0,2 0,32 0,78 0,35 0,62 1,61 0,54 1 1,5 1,04 0,85 0,77 0,48 1,96 11,5 19 10,6 698,3 21,2 23,5 16,1 40,4 12,4 3,8 2,6 47,2 24,1 12,9 79,6 15,2 11,4 22,4 16,2 15,7 17,7 11,6 14,3 27,9 16 13,6 61,8 25,4 13,4 12,6 17,1 14,4 22 11,8 26,9 17,8 40,5 14 26,6 14,5 13,7 13,3 24,1 12,7 26,7 300,2 2,66 3,58 2,47 3,11 1,59 3,53 3,74 2,47 4,01 0,48 1,48 2,94 0,82 2,1 1,65 1,53 3 4,15 0,6 0,68 2,1 3,76 1,7 0,61 3,61 1,48 3,94 1,8 5,31 2,13 1,02 1,95 2,99 1,28 2,7 1,8 4,87 1,75 2,39 1,37 2,54 1,94 4,53 1,21 2,65 2,59 1,58 1,01 0,9 0,66 1,2 0,5 1,19 1,69 0,6 2,12 0,5 0,36 1,35 0,16 1 1,6 0,9 1,2 0,6 0,18 1,08 2,13 1 0,68 1,08 1,34 0,35 1,33 1,67 0,24 0,63 0,32 0,74 0,92 0,11 1 0,3 1,75 0,09 0,59 0,24 0,4 1,1 0,79 0,16 0,8 0,56 0,76 14,5 6,4 16 16,2 26 16,3 26,6 8,3 17,2 90,7 25,2 18 22,4 18,3 14,2 14,4 14,5 9,8 21,7 34,2 26,9 17,1 35,4 56,2 12,4 16,3 14,7 12 17 13,4 17 24,6 17,4 27,2 13 19,5 11,5 8,2 14,2 23 17 16,1 10,7 29 15,5 17 19,8 2,03 1,04 1,87 0,97 1,36 1,55 1,57 0,42 0,51 0,94 0,35 0,98 1,12 1 17,2 35,7 16,9 20,5 27,2 24,9 17 Signature Assignment Grading Guide QNT/561 Version 9 Applied Business Research and Statistics Copyright Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved. University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries. Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation. Edited in accordance with University of Phoenix® editorial standards and practices. Signature Assignment Grading Guide QNT/561 Version 9 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 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 Met Partially Met Not Met Comments: 2 Signature Assignment Grading Guide QNT/561 Version 9 Content 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 Met Partially Met Not Met Comments: 3 Signature Assignment Grading Guide QNT/561 Version 9 Content Met Partially Met Not Met Total Available Total Earned 13 #/13 Partially Met Not Met Total Available Total Earned 3 #/3 Comments: 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? Writing Guidelines Met 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. Comments: 4 Signature Assignment Grading Guide QNT/561 Version 9 Assignment Total Additional comments: # 16 #/16 5 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 Endof-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 Copyright © 2017 by University of Phoenix. All rights reserved. 1 Week 6 Options QNT/561 Version 9 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 © 2017 by University of Phoenix. All rights reserved. 2
Purchase answer to see full attachment
User generated content is uploaded by users for the purposes of learning and should be used following Studypool's honor code & terms of service.

Explanation & Answer

Kindly see attached a 1630-word essay with the statistical report following the outline provided in the grading rubric and the corresponding plagiarism report

WEEK 6 ASSIGNMENT: SIGNATURE

1

WEEK 6 ASSIGNMENT: SIGNATURE
(NAME)
(PROFESSOR’S NAME)
(COURSE)
(DATE)

WEEK 6 ASSIGNMENT: SIGNATURE

2

The present report details the analysis carried out of the data contained in the Consumer
Food database as part of the job at the analytics department in a consulting company obtained
after having successfully completed the MBA studies.

Part 1.
The Consumer Food database contains the information related to the annual food
spending, the annual household income and the non-mortgage annual debt of a total of 200
houses located in different regions of the USA and in different locations. In this regard, the
database is supposed to contain a representative sample of the population of the households
located in the Northeast, Midwest, South and Western regions of the United States. These
households are classified according to their metropolitan or outside metropolitan location.
The main objective of the current analysis was to determine if the annual food spending
of households located in the Midwest region of the country was significantly higher or not than
the US national average. Additionally, the database needed to be characterized from a descriptive
point of view to evaluate the characteristic measures of both central tendency (including the
evaluation of the mean, median and mode) and variability (including the calculation of the
standard deviation, variance, range, coefficient of variation and the five number summary).
To perform such analyses, the database consists of a total of five different columns. The
first three columns contain quantitative data regarding the annual food spending, the annual
household income and the non-mortgage annual debt of the different households. The level of
measurement of the data contained in these columns is therefore interval. The remaining two
columns, on the other hand, contain qualitative data regarding the location of the household
(either in the metropolitan or outside the metropolitan area) and the region of the household

WEEK 6 ASSIGNMENT: SIGNATURE

3

(which can be placed in the Northeast, the Midwest, the West and the South regions of the
country).
The questions addressed are:
-

Which are the characteristic measures of central tendency of the data contained in the
database?

-

Which are the characteristic measures of variability of the data contained in the database?

-

Does the database contain any outlier?

-

Is the annual food spending of the houses located in the Midwest region higher than the
national average of $8,000.00?

-

Is there any difference between households located in the metropolitan area and those
outside the metropolitan area regarding their annual food spending?

-

Does the region have any influence on the annual food spending, annual household
income or the non-mortgage debt?

Part 2.
The descriptive analysis carried out is based on the evaluation of the characteristic
measures of central tendency and variability of the different variables contained in the database
and the analysis of outliers.
The outcome from these analyses are summarized in tables 1 and 2, and in figure 1. In
this regard, table 1 presents the evaluation of the mean, median and mode as characteristic
measures of central tendency. Additionally, it includes information about the calculation of the
characteristic measures of variability, such as the standard deviation, variance, range, coefficient
of variation, and the five-number summary. Table 2, on the other hand, presents the outcome
from the analysis of outliers by considering as outlier any result that lies outside the 99%

WEEK 6 ASSIGNMENT: SIGNATURE

4

confidence interval for the mean values of the different variables under study. Finally, figure 1
summarizes the analysis of the descriptive statistics of the data contained in the database in a
graphical way. In this regard, the box and whisker plots presented in such figure provide
information related to the central tendency measures, the variability of the results, and the
presence of the identified outliers.
Table 1. Summary of the results obtained for the descriptive statistics of the quantitative
variables

Table 1 shows how the mean and the median values are close one to each other,
indicating that the assumption of normality might be valid. On the other hand, the mode does not
seem to be a representative measure of central tendency, due to the small sample size and big
variability of results. The mode is the best descriptor of central tendency for the qualitative
variables, for which the database indicates that the mode is the Northeast region and the
metropolitan area.

WEEK 6 ASSIGNMENT: SIGNATURE

5

Table 2. Identification of outliers

Table 2 represents the calculated 99% confidence intervals for each of the variables and
the resulting outliers. These 99% confidence intervals have been calculated by applying the
equation μ±2.575*σ where μ represents the mean value and σ the standard deviation. The value
of 2.575 is the z value corresponding to a probability of 99% and that therefore accounts for the
desired confidence level. Any value outside these intervals is considered an outlier since there is
only a 1% chance that it is part of the analyzed sample (Ashanulla, 2003). It is interesting to note
how the only outlier present in the database corresponds to one household, that has both an
unexpectedly high annual food spending and annual household income.

Figure 1. Box and whisker plot of the three quantitative variables contained in the database. The
boxes represent the data located between the first and third quartile with the middle box
representing the median. The whiskers correspond to the percentiles 1st-25th and 75th-99th.
Identified outliers are marked by an asterisk

WEEK 6 ASSIGNMENT: SIGNATURE

6

Part 3.
Evaluation of the annual food spending in Midwestern houses
A hypothesis test has been conducted to evaluate if the annual food income of
Midwestern houses is higher than the national average. In this regard, a subsample has been
selected where only the houses located in the Midwest.
A t test hypothesis has been carried out considering that the subsample size is relatively
small, as it includes only the 45 households located in the Midwest, and that the population’s
standard deviation for the annual food spending is unknown (O’Hagan & Forster, 2009). The
outcomes from the hypothesis test are presented in table 3.
Table 3. Summary of the outcome of the hypothesis test carried out

As can be observed, the resulting p-value is of 0.032. Considering that this value is higher
than the desired significance level of 0.01, there is not enough evidence to support the rejection
of the null hypothesis. Taking this into account, the mean annual food spending in Midwestern
houses is not significantly higher than the national average and the small difference observed can
be attributed to random.

WEEK 6 ASSIGNMENT: SIGNATURE

Evaluation of the effect of the location of the house in the annual food spending
A hypothesis test has been conducted to evaluate if the annual food income of
metropolitan and outside metropolitan areas are different. In this regard, the sample has been
divided into metropolitan households and outside metropolitan households. The outcomes from
the hypothesis test are presented in table 4.
Table 4. Summary of the outcome of the hypothesis test carried out

As can be observed from the outcome of the hypothesis test presented in table 4, the
resulting p-value is of 0.0089. Considering that this value is lower than the desired significance
level of 0.01, there is enough evidence to support the rejection of the null hypothesis, meaning
that the location of the house (in the metropolitan area or outside it) has a direct influence on the
annual food spending.
Effect of the region on the annual food spending, annual household income and non-mortgage
debt
Three independent one way ANOVA tests have been conducted to evaluate if the region
had any influence on any of the quantitative variables contained in the database. The outcome

7

WEEK 6 ASSIGNMENT: SIGNATURE

from these ANOVA tests is presented in tables 5-7 together with the descriptive characteristics
of each of the variables according in the different regions.
Table 5. ANOVA test for the evaluation of the effect of the region on the annual food spending

Table 6. ANOVA test for the evaluation of the effect of the region on the annual household
income

8

WEEK 6 ASSIGNMENT: SIGNATURE

9

Table 7. ANOVA test for the evaluation of the effect of the region on the non-mortgage debt

As can be observed, the p-values resulting from the one-way ANOVA analysis are below
than 0.01 in tables 5 and 6 and above 0.01 in table 7. This result indicates that the region in
which the households are located has a significant influence on the non-mortgage debt (therefore
resulting in a lower p value), whereas it does not have such a significant influence in the annual
food spending or the annual household income. However, considering the relatively small
differen...


Anonymous
Really helpful material, saved me a great deal of time.

Studypool
4.7
Trustpilot
4.5
Sitejabber
4.4

Related Tags