Signature Assignment

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timer Asked: Jun 28th, 2018
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Question description

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.

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
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
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
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 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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

Tutor Answer

RyanTopTutor
School: University of Maryland

Attached.

Varance
Region: 1 Location: Varance
Varance
and
Annual
Annual
Non
= NE 2 = 1 = Metro
and
and
standard
Food
Househol mortgage MW 3 =
2=
standard standard deviation
Spending d Income household S
4 = Outside deviation deviation
of
Outlier of
($)
($)
debt ($)
W
Metro
of A.F.S
of A.H.I
NM.H.D. variable 1
8909
56697
23180
1
1
3249 1312047.1 57393919 FALSE
5684
35945
7052
1
1
10771524 384415425 73138823 FALSE
10706
52687
16149
1
1
3027600 8209196.9 296845.6 FALSE
14112
74041
21839
1
1
26481316 341850847 38877185 FALSE
13855
63182
18866
1
1
23902321 58214648 10640397 FALSE
15619
79064
21899
1
1
44262409 552835970 39628481 FALSE
2694
25981
8774
1
1
39337984 874471485 46655674 FALSE
9127
57424
15766
1
1
25921 3504407.7 26296.53 FALSE
13514
72045
27685
1
1
20684304 272027223 1.46E+08 FALSE
6314
38046
8545
1
1
7033104 306449783 49831685 FALSE
7622
52408
28057
1
1
1806336 9886281.4 1.55E+08 FALSE
4322
41405
6998
1
1
21566736 200130694 74068912 FALSE
3805
29684
4806
1
1
26635921 669154448 1.17E+08 FALSE
6674
49246
13592
1
1
5253264 39764683 4049699 FALSE
7347
41491
4088
1
1
2621161 197699842 1.33E+08 FALSE
2911
26703
15876
1
1
36663025 832278844 74020.2 FALSE
8026
48753
16714
1
1
883600 46228761 1231181 FALSE
8567
55555
16783
1
1
159201 12.087748 1390665 FALSE
10345
71483
21407
1
1
1901641 253808983 33677705 FALSE
8694
50980
19114
1
1
73984 20907047 12318852 FALSE
8821
46403
7817
1
1
21025 83702315 60642258 FALSE
8678
51927
14415
1
1
82944 13138056 1414746 FALSE
14331
84769
17295
1
1
28783225 853636425 2861069 FALSE
9619
59062
16687
1
1
426409 12319194 1172755 FALSE
9286
57952
14161
1
1
102400 5761276.2 2081959 FALSE
8206
58355
19538
1
1
577600 7855231.8 15476707 FALSE
16408
81694
15187
1
1
55383364 683421509
173937 FALSE
12757
69522
14651
1
1
14371681 195172152 907970.8 FALSE
17740
96132
0
1
1
76983076 1.647E+09 2.43E+08 TRUE
7739
57796
22057
1
1
1505529 5035655.5 41642873 FALSE
15383
88276
1896
1
1
41177889 1.071E+09 1.88E+08 FALSE
4579
32264
7979
1
1
19245769 542348387 58133445 FALSE
11679
65928
0
1
1
7360369 107670343 2.43E+08 FALSE
12877
69924
27330
1
1
15295921 206557432 1.37E+08 FALSE
16232
91108
9876
1
1
52794756 1.264E+09 32812663 FALSE
9621
54070
19908
1
1
429025 2195398.6 18520314 FALSE
8171
47238
17819
1
1
632025 69118365 4905710 FALSE
12128
77427
31340
1
1
9998244 478494721 2.48E+08 FALSE
8642
59805
4963
1
1
104976 18091732 1.13E+08 FALSE
12400
...

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Review

Anonymous
Excellent job

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