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About Your Signature AssignmentThis signature assignment is de.docx
- 1. About Your SignatureAssignment 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 12 paragraphs each 150 words statistical report including the following: · Explain the context of the case · Provide a research foundation for the topic · Present graphs
- 2. · 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,
- 3. 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?
- 4. · State theinterpretations 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? The length is 5 pages Format your assignment consistent with APA format. Click the Assignment Files tab to submit your assignment. 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
- 5. in the manufacturingdatabase 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
- 6. employees in thehospitals 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
- 7. are normally distributedin 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. Title ABC/123 Version X 1 Week 6 Options QNT/561 Version 9 1 University of Phoenix MaterialOption 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
- 8. 1000. Three variables,Value Added by Manufacture, Cost of Materials, and End-of-Year Inventories, are in million-dollar units. The Industry Group variable consists of numbers from 1 to 20 to denote the industry group to which the particular subindustry belongs. Option 2: Hospital Database This database contains observations for six variables on U.S. hospitals. These variables include Geographic Region, Control, Service, Census, Number of Births, and Personnel. The region variable is coded from 1 to 7, and the numbers represent the following regions: 1 = South 2 = Northeast 3 = Midwest 4 = Southwest 5 = Rocky Mountain 6 = California 7 = Northwest Control is a type of ownership. Four categories of control are included in the database: 1 = government, nonfederal 2 = nongovernment, not-for-profit 3 = for-profit 4 = federal government
- 9. Service is thetype of hospital. The two types of hospitals used in this database are: 1 = general medical 2 = psychiatric Option 3: Consumer Food The consumer food database contains five variables: Annual Food Spending per Household, Annual Household Income, Non- Mortgage Household Debt, Geographic Region of the U.S. of the Household, and Household Location. There are 200 entries for each variable in this database representing 200 different households from various regions and locations in the United States. Annual Food Spending per Household, Annual Household Income, and Non-Mortgage Household Debt are all given in dollars. The variable Region tells in which one of four regions the household resides. In this variable, the Northeast is coded as 1, the Midwest is coded 2, the South is coded as 3, and the West is coded as 4. The variable Location is coded as 1 if the household is in a metropolitan area and 2 if the household is outside a metro area. The data in this database were randomly derived and developed based on actual national norms. Option 4: Financial Database The financial database contains observations on seven variables for 100 companies. The variables are Type of Industry, Total Revenues ($ millions), Total Assets ($ millions), Return on Equity (%), Earnings per Share ($), Dividends per Share ($), and Average Price per Earnings (P/E) ratio. The companies represent seven different types of industries. The variable Type displays a company's industry type as: 1 = apparel
- 10. 2 = chemical 3= electric power 4 = grocery 5 = healthcare products 6 = insurance 7 = petroleum Copyright © XXXX by University of Phoenix. All rights reserved. Copyright © 2017 by University of Phoenix. All rights reserved. Option 1 - ManufacturerSIC CodeNo. Emp.No. Prod. Wkrs.Value Added by Mfg.Cost of MaterialsEnd Yr. Inven.Indus. Grp.2014333702351878713363012021318315724427743157120 32041692450627222873212041007021667370403407120522013 72071212030115512068969126401367436131207261842581913 01946120814372352103352171991209171126205481961231351 21121152344255575506221232287163422213221508314155221 46462426225542221524724714219929322274634307535714273 22313126731061325322417138177072673225169147898610421 20833226514131454140697322755444076712514463228847638 06899410143229614742765504129132312722123971635642322 00178942389262314423329425011045111212727423438321916 22836824235171459936419742363428206318134504237113471 17423831251445132152642392241791060312376274742418368 57759661578524217214710404192853979524325720913274186 32332952445143190921703555245826846067290580524994785 51881351604525127323312464129803535625270535447401182 96253372922905101447625481614182375595662595439281826
- 11.
- 12. 27214129028180287681193842681573105116787776119385271 72390102042619386613614032811422901938764415382177193 91433027613646145120393131068550632820394103768327660 42608203953526264317897992039624191406997415203991791 23111998530286120 Option 2 -HospitalHospitalGeog. RegionControlServiceCensusBirthsPersonnel1121107312792211 11981077176231213561027231041111003553285711916818164 21159381010777441657357428421481131912125317331594101 11212572331111127169241126313043020313631430325146212 33204967615641221134716611111679176318426485051862121 92450154319631112146575520631124095921631501993325226 21142227595423621111149410912461114013136712563128451 30026621154168975327621150158360728631144201792929631 42995354306217720454083152111916861251325212750338633 52115126144342211792026204735221175141213433622146115 17172337132320963812174052939111414271936944012125310 74104241131180142110714211118476215254312124331941983 44121115496670451112151442165346132480167471311241107 79348121189298984149111181113316501119093511312803735 21212881732635311110810649435412115475960555721761317 59656731165175111655731229505685833110105075932169714 47960321129913661321185224314566232137839663486633211 14130888564332490243653211062514100166321460371433016 73214312633768341295561193693211251327116170321174153 22713111021618572331143392057331117312171224743212072 64117047532122379081576321825207127731164351567832113 91168176979321109793875803122980790813315203088231134 14708331216804948433221011185141390016188611147024487 12180776525881315045147289132113094901214514529791111 76128484792131129123493221603194019422141821543928952 21172951989622113849612319722164589545982216280666399 21113170182010022126539682581101342456012981023224001 26103311310365525341043317202511053321908510634111204 32107312375086410833215066109321783063556110311123169 34711132154662391123219682797311313182570439114112110
- 13. 60184911511130010211631256026211734136342885118331127 49454911931218006111203415903301215211270147112251137 07512354113286262124521100235328125331473393771263111 94398575127321172127519161285315165699262012953112013 64571130511179714703131241140053513223278016013323268 02021342211867791330135221910370136211340220231231375 11254334627451385211081071815139521613525761402211742 54502141212306080814223228050143221395699728144221923 24624087145211335331130121461214606814711131642073090 14814241601358149111743395761501218613028415132138911 45152321147114323121533422320112415431213803361553213 85094151563212451026177915731217103381583315144745315 93412811614371603127970261161721569226091627116956264 71637114078611647411630207416572123121222232166212523 09481672413104091682224301531692216671074117022123111 65162517114111466538172131144110678917313143376395174 34118509561753218263736217612249014417713124352229178 13163447396179121274122722561801319396373118114186303 81477182132280102183132250106184131181868939185531391 18939218651130228493516187521801728785188521632171607 18922131364273190222170063019111120329931379192121296 01108193131831964583194721846015141957112938721619672 11871946159319772177545105519851210403991995118583883 42005114751104 Option 3 -Consumer FoodAnnual Food Spending ($)Annual Household Income ($)Non mortgage household debt ($)Region: 1 = NE 2 = MW 3 = S 4 = WLocation: 1 = Metro 2 = Outside Metro890956697231801156843594570521110706526871614911 14112740412183911138556318218866111561979064218991126 94259818774119127574241576611135147204527685116314380 46854511762252408280571143224140569981138052968448061 16674492461359211734741491408811291126703158761180264 87531671411856755555167831110345714832140711869450980 19114118821464037817118678519271441511143318476917295 11961959062166871192865795214161118206583551953811164
- 14.
- 15. 86341576238407188674111617786271189441989547710229304 11629364443316874181855887135424411397287954115494111 24354778125524146353982519494411006349536121954184266 01021378741743649139223564111747510524553411539770500 12025416842548941621741967860570410641128525762531228 41101145695625907418496614001093416689505321710641156 96727741779341984169981216074112529668911768941102106 74311999541886864782144894164263898717864411109664867 58394110086504218689412587270761753441124925178420284 42845654135220374268015329123342426339498043494342780 25220528579429717728412234942602646238201654256184593 81053842102177771618516428338597117980429048421061978 64240173646299354210906534031817742151487129066964288 30667592097242848157616287674211358762211373421055378 20259204269695516424795421321961171214824235433409325 96942732650647107504284585989822940421176652884259704 2990873629711242 Option 4 -FinancialCompanyTypeTotal RevenuesTotal AssetsReturn on EquityEarnings per ShareDividends per ShareAverage P/E RatioAFLAC672512945417.12.080.2211.5Albertson's41469052 1921.42.080.6319Allstate6201068091820.13.560.3610.6Amerad a Hess7834079350.20.080.6698.3American General63362806207.12.191.421.2American Stores419139853612.21.010.3423.5Amoco7362873248916.72.7 61.416.1Arco Chemical2399541166.21.142.840.4Ashland71431977779.53.81. 112.4Atlantic Richfield7192722532221.85.412.833.8Bausch & Lomb51916277360.891.042.6Baxter International56138870711.51.061.1347.2Bristol-Myers Squibb5167011497744.43.141.5224.1Burlington Coat1177777512.31.180.0212.9Central Maine Power395422992.40.160.979.6Chevron7419503547318.64.952.2 815.2CIGNA61493510819913.74.881.111.4Cinergy3435388581 3.31.591.822.4Dayton Hudson12775714191181.70.3316.2Dillard's1681755929.22.310.
- 16. 1615.7Dominion Resources37678201937.92.152.5817.7Dow Chemical2200182404023.67.73.2411.6DPL31356358513.91.20. 9114.3E. I.DuPont DeNemours2466534294221.32.081.2327.9Eastman Chemical24678577816.33.631.7616Edison International392352510112.31.73113.6Engelhard2363125866.10 .330.3861.8Entergy39562270014.21.031.825.4Equitable696661 5143812.32.860.213.4Ethyl71064106753.60.710.512.6Exxon713 72429606419.43.371.6317.1FPL Group363691244912.23.571.9214.4The GAP16508333833.71.30.222Georgia Gulf29666132282.390.3211.8GIANT Food4423115227.91.180.7826.9A & P41026229956.91.660.3517.8Great Lakes Chemicals2131122705.51.190.6240.5Green Mountain Power Company31793268.31.571.6114Hannaford Bros.4322612279.91.40.5426.6Hercules218662411473.18114.5 Houston Industries368731841581.661.513.7Jefferson- Pilot625782313114.53.471.0413.3Johnson & Johnson5226292145326.72.410.8524.1Liberty6660318511.13.34 0.7712.7The Limited19189430110.60.790.4826.7Lincoln National64899771750.40.211.96300.2Lubrizol216741462192.66 1.0114.5Lyondell Petrochemical73010155946.23.580.96.4Mallinkrodt5186829881 4.82.470.6616May Department Stores112685993020.53.111.216.2McKesson5208575608111.59 0.526Mercantile Stores1314421787.93.531.1916.3Merck5236372581236.63.741. 6926.6Millennium Chemicals23048432612.62.470.68.3Mobil7659064355916.84.01 2.1217.2Monsanto27514107747.20.480.590.7Morton223882805 12.31.480.3625.2Murphy Oil72138223812.32.941.3518Mylan Laboratories555584813.50.820.1622.4NALCO Chemical214341441252.1118.3Nevada Power3799233910.11.651.614.2NIPSCO32587493714.11.530.91 4.4Olin22410194617.431.214.5Orion
- 17. Capital615913884164.150.69.8Owens & Minor531177139.40.60.1821.7Pacific Corporation36278138805.20.681.0834.2J. C. Penney130546234937.72.12.1326.9Pennzoil72654440615.83.76 117.1Pfizer5125041533627.91.70.6835.4Pharmacia& Upjohn56710103805.80.611.0856.2Phillips Petroleum7154241386019.93.611.3412.4Poe & Brown612919425.11.480.3516.3PPG27379686828.53.941.3314. 7PP&L Resources33049948511.41.81.6712Progressive64190756018.75. 310.2417Rohm & Haas23999390019.82.130.6313.4Ruddick4230088512.51.020.32 17Schering-Plough56778650751.21.950.7424.6Sears, Roebuck1412963870020.32.990.9217.4Stryker598098520.51.28 0.1127.2Sun7105314667182.7113Sunamerica621143563714.71. 80.319.5Texaco7466672960020.94.871.7511.5The TJX Companies17389261026.31.750.098.2Torchmark622831096717. 52.390.5914.2Tosco713282597510.91.370.2423Travelers637609 38655514.92.540.417Ultramar Diamond Shamrock71088255959.51.941.116.1Union Carbide26502696428.84.530.7910.7United States Surgical Corporation5117217267.51.210.1629UNOCAL76064753028.92. 650.815.5UNUM640771320015.22.590.5617USX- Marathon7157541056512.61.580.7619.8Valero Energy7575624939.62.030.4217.2Warner- Lambert58180803130.71.040.5135.7WEIS Markets418199729.21.870.9416.9Wellman2108313194.80.970.3 520.5Winn-Dixie Stores413219292115.31.360.9827.2WITCO221872298141.551.1 224.9Zenith Nation Insurance660112527.81.57117