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TitleABC123 Version X1Part 3 Inferential Statistics.docx
- 1. Title ABC/123 Version X 1 Part3 Inferential Statistics QNT/561 Version 9 1 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
- 2. 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
- 3. Household Debt brokendown by Region and Location. Using Region as an independent variable with four classification levels (four regions of the U.S.), perform three different one- way ANOVA's—one for each of the three dependent variables (Annual Food Spending, Annual Household Income, Non- Mortgage Household Debt). Did you find any significant differences by region? Option 4: Financial Database 1. Use this database as a sample and estimate the earnings per share for all corporations from these data. Select several levels of confidence and compare the results. 2. Are the average earnings per share for companies in the stock market less than $2.50? Use the sample of companies represented by this database to test that hypothesis. Let α = .05. 3. Test to determine whether the average return on equity for all companies is equal to 21. Use this database as the sample and α = .10. Assume that the earnings per share and return on equity are normally distributed in the population. 4. Do various financial indicators differ significantly according to type of company? Use a one-way ANOVA and the financial database to answer this question. Let Type of Company be the independent variable with seven levels (Apparel, Chemical, Electric Power, Grocery, Healthcare Products, Insurance, and Petroleum). Compute three one-way ANOVAs, one for each of the following dependent variables: Earnings Per Share, Dividends Per Share, and Average P/E Ratio. Copyright © XXXX by University of Phoenix. All rights reserved. Copyright © 2017 by University of Phoenix. All rights reserved.
- 4. 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 94718626115112201327972572621169018848205964257726355 42965510604150272652121631566824634397672672321822591 82896354277271403136306928483894827212116179826940121 68273136571785788633736827469259699282387482756044373 84072957243008276412838783811688827721123989104757782 78655043882055504827955394055109823682818045165671129 82644928211579250253459661929283213106598132718711533 92841267531801199324535928551288497984921789286126752 88864693585779287372412277111302354928976451154713085 27499291674326006132880107181029525183464618265810299 14821874446670103016554707970911067113028744249617511 30561464528380510571130612295727571951411113087635985 56215726411874113111512131318654041231332162163351231 43731190716827161231522538562123166474739519912317873 28255751231976233177401232112917179432821332260516532 35271505133236450485042548831332417133509228282813325 31252176138770013326453626961183600133272051521573917
- 5. 01019661332817139995652631332972537838543216521333122 11742918045696121981433212810690616913154314333352642 00111841834143341511141057356941433516212316670318926 37714336947958564696938143393223316427908001434133273 99993641453153421401071175087203124153434532441235271 12115344432315279743152772041534510481693649091768153 46259211198802153139971534712999779362321181153484024 35281689107715349300219217181927364601535179551051312 95436791635294709545118583339163532051331817823474734 41635429521122673143436730163551921101922116515682316 35626517223110185437898163572599641135608571027716358 20114717521218194857163593922932532213897496416361745 16700552314951736217112014278126573887173631088794661 25782299173641571171342811065307617365493734597621107 01736625812038705295919467173675883688405944486131451 73691511061392013398351417371772634105899223639158521 83723771904522042367368141837314110879037760216518374 31232590436312331837518141435167441218376812999868120 47701837947353564547611021838118668210718760618319382 27214129028180287681193842681573105116787776119385271 72390102042619386613614032811422901938764415382177193 91433027613646145120393131068550632820394103768327660 42608203953526264317897992039624191406997415203991791 23111998530286120 Option 2 -HospitalHospitalGeog. RegionControlServiceCensusBirthsPersonnel1121107312792211 11981077176231213561027231041111003553285711916818164 21159381010777441657357428421481131912125317331594101 11212572331111127169241126313043020313631430325146212 33204967615641221134716611111679176318426485051862121 92450154319631112146575520631124095921631501993325226 21142227595423621111149410912461114013136712563128451 30026621154168975327621150158360728631144201792929631 42995354306217720454083152111916861251325212750338633 52115126144342211792026204735221175141213433622146115 17172337132320963812174052939111414271936944012125310
- 6.
- 7. 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 08816941518711127576952214651111774096132011773957796 22057111538388276189611457932264797911116796592801112 87769924273301116232911089876119621540701990811817147 23817819111212877427313401186425980549631112400603346 63211918554114185931278624068015202129775582631486126 77152008217131230593964312179121321170309132211274084 64505602121158176140338741214233808331147812335231899 27621226302164726631290936592411355121265265923513212 95596281112613126112423353149121043165134151961212630 64621214331245783655355021295516291011376121026270727 13287129551576341185721101435654916136218955596621162 72110197573501843221112345644710871219320611360219089 51526490221123007997917270211148466733151452111215753 59156112172044079589752155793912865762111723754821250 82193536399802177614584566712142613822385762198306678 71178211238677852936218673558251416721109445702290182 19910642631276821992875881174232142643434321323217971
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- 9. 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. 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
- 10. Houston Industries368731841581.661.513.7Jefferson- Pilot625782313114.53.471.0413.3Johnson & Johnson5226292145326.72.410.8524.1Liberty6660318511.13.34 0.7712.7TheLimited19189430110.60.790.4826.7Lincoln 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 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.
- 11. 52.390.5914.2Tosco713282597510.91.370.2423Travelers637609 38655514.92.540.417Ultramar Diamond Shamrock71088255959.51.941.116.1Union Carbide26502696428.84.530.7910.7United StatesSurgical 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 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 1000. Three variables, Value Added by Manufacture, Cost of Materials, and End-of-Year Inventories, are in million-dollar
- 12. units. The IndustryGroup 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
- 13. in this databaseare: 1 = general medical 2 = psychiatric Option 3: Consumer Food The consumer food database contains five variables: Annual Food Spending per Household, Annual Household Income, Non- Mortgage Household Debt, Geographic Region of the U.S. of the Household, and Household Location. There are 200 entries for each variable in this database representing 200 different households from various regions and locations in the United States. Annual Food Spending per Household, Annual Household Income, and Non-Mortgage Household Debt are all given in dollars. The variable Region tells in which one of four regions the household resides. In this variable, the Northeast is coded as 1, the Midwest is coded 2, the South is coded as 3, and the West is coded as 4. The variable Location is coded as 1 if the household is in a metropolitan area and 2 if the household is outside a metro area. The data in this database were randomly derived and developed based on actual national norms. Option 4: Financial Database The financial database contains observations on seven variables for 100 companies. The variables are Type of Industry, Total Revenues ($ millions), Total Assets ($ millions), Return on Equity (%), Earnings per Share ($), Dividends per Share ($), and Average Price per Earnings (P/E) ratio. The companies represent seven different types of industries. The variable Type displays a company's industry type as: 1 = apparel 2 = chemical
- 14. 3 = electricpower 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.