# Register now to access 7 million high quality study materials (What's Course Hero?) Course Hero is the premier provider of high quality online educational resources. With millions of study documents, online tutors, digital flashcards and free courseware, Course Hero is helping students learn more efficiently and effectively. Whether you're interested in exploring new subjects or mastering key topics for your next exam, Course Hero has the tools you need to achieve your goals.

32 Pages

### 05ProbDist

Course: EXST 7087, Fall 2009
School: LSU
Rating:

Word Count: 1090

#### Document Preview

Techniques Statistical I EXST7005 Probability distributions You are here Probability s PROBABILITY - a measure of the likelihood of the occurrence of some event An event can be any outcome (e.g. verbal, mathematical, graphical) Some rules of Probability s If the event is certain to occur, the probability is (one, unity). P(A) s If the event is certain to NOT occur, the probability is 0 (zero, null) P(A)...

Register Now

#### Unformatted Document Excerpt

Coursehero >> Louisiana >> LSU >> EXST 7087

Course Hero has millions of student submitted documents similar to the one
below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.

Course Hero has millions of student submitted documents similar to the one below including study guides, practice problems, reference materials, practice exams, textbook help and tutor support.
Find millions of documents on Course Hero - Study Guides, Lecture Notes, Reference Materials, Practice Exams and more. Course Hero has millions of course specific materials providing students with the best way to expand their education.

Below is a small sample set of documents:

LSU - EXST - 7087
Statistical Techniques IEXST7005The Z distributionYou are still hereObjectivesThe first statistical distribution we will use anddevelop for hypothesis testing is the Zdistribution.This will require an understanding of thedistribution,Of how to
LSU - EXST - 7087
Statistical Techniques IEXST7005Distribution of Sample MeansOBJECTIVESsUsually we will be testinghypotheses about means. We willneed some additional informationabout the nature of means ofsamples in order to do hypothesistests.Distribution of S
LSU - EXST - 7087
Statistical Techniques IEXST7005Exam 1 CoverageRange of CoveragesMaterial covered will be from,Introduction, including the Scientific Method anddefinition of terms, through T-tests of hypothesis and use of the formula for calculating sample size. I
LSU - EXST - 7087
Statistical Techniques IEXST7005Confidence IntervalsConfidence intervalsAn expression of what we believe to be a rangeof values that is likely to contain the true value osome parameter is called a confidence interval.sWe can calculate confidence i
LSU - EXST - 7087
Statistical Techniques IEXST7005Linear CombinationsLinear combinationsThis is a function of random variables of the formaiYi where ai is a constant and Yi is a variable.sGeneric Example: We want to create a score wecan use to evaluate students app
LSU - EXST - 7087
Statistical Techniques IEXST7005Factorial Treatments &amp; InteractionsThe Factorial TreatmentArrangementsAlso known as &quot;two-way&quot; ANOVAThis analysis has two (or more) Treatments, forexample treatment A with two levels (a1 and a2)and treatment B with
LSU - EXST - 7087
Statistical Techniques IEXST7005Miscellaneous ANOVA Topics &amp; SummaryLSMeans calculationThe calculations of LSMeans is different. For abalanced design, the results will be the same.However, for unbalanced designs the results wioften differ.sThe ME
LSU - EXST - 7087
Statistical Techniques IEXST7005Simple Linear RegressionSimple Linear RegressionsMeasuring &amp; describing a relationship betweentwo variablesSimple Linear Regression allows a measure of therate of change of one variable relative to anothervariable.
LSU - EXST - 7087
Statistical Techniques IEXST7005Multiple RegressionMultiple RegressionMultiple Regression s The objectives are the same. Testing hypotheses about potential relationships (correlations), fitting and documenting relationships, and estimating parameters
Troy - MANAGEMENT - 101
fName: Nguyen Thi Lan ThanhStudent ID: 1236311CHAPTER 16Questions:16.2/ Define cash conversion cycle (CCC) and explain why, holding other things constant, afirms profitability would increase if it lowered its CCC.Cash conversion cycle (CCC): The len
Utah State - FWE - eewe
MATF_Z01.qxd2/23/0918:07Page 645APPENDIX 1Differentiation fromFirst PrinciplesWe hinted in Section 4.1 that there was a formal way of actually proving the formulae forderivatives. This is known as differentiation from rst principles and we begin b
Utah State - MGT - 2010
Name: _ Class: _ Date: _ID: AMT2050 NAU Week 2 Chapter 1 &amp; 2 QuizMultiple Choice Identify the letter of the choice that best completes the statement or answers the question. _ 1. Which of the following is not a function of management? a. Plan b. Contro
Utah State - MGT - 2010
Name: _ Class: _ Date: _ID: AMT2050 NAU Week 2 Chapter 3, 4, &amp; 5Multiple Choice Identify the letter of the choice that best completes the statement or answers the question. _ 1. In the _ stage, companies may opt for a multinational approach. a. interna
Utah State - MGT - 2010
Name: _ Class: _ Date: _ID: AMT2050 Week 4 Quiz Chapter 6Multiple Choice Identify the letter of the choice that best completes the statement or answers the question. _ 1. Which of these refers to the process of identifying problems and then resolving t
Utah State - MGT - 2010
Name: _ Class: _ Date: _ID: AWeek 5 MT2050 QuizMultiple Choice Identify the letter of the choice that best completes the statement or answers the question. _ 1. Which of these is the degree to which organizational tasks are subdivided into individual j
Utah State - MGT - 2010
Name: _ Class: _ Date: _ID: AMt2050 Quiz Week 7 Chap 9-11Multiple Choice Identify the letter of the choice that best completes the statement or answers the question. _ 1. The practice of hiring or promoting of applicants based on criteria that are not
Utah State - ECON DEPAR - Economics
Page iiiIndustrial OrganizationTheory and ApplicationsOz ShyThe MIT PressCambridge, MassachusettsLondon, EnglandPage ivCopyright 1995 Massachusetts Institute of TechnologyAll rights reserved. No part of this book may be reproduced in any form by
Utah State - ECON DEPAR - Economics
Question AnswerThe nature of management is to cope with _ and far-reaching challenges. a.simple b.planned c.diverse d. organized e. controlled C. DiverseManagers, in today's work environment, rely less on_and more on_ coord&amp;commun; control&amp;command comma
Globe - ECON - 229
A:\UMN\AI\findintersection.lispWednesday, November 09, 2011 3:21 AM; Balaji, FNU; Student ID: 4287938; Extra Credit Assignment 4; The algorithm tries to find if 2 given lines represented by ax+by+c = 0; intersect or not. It also tries to talk about
Jefferson College - QM - 670
ABCDEFGHI1INVENTORY ANALYSIS - ECONOMIC ORDER QUANTITY MODEL23 PROBLEM: House of Fine Wines and Liquors - Tres Equis Beer41.EntertheproblemnameinB3.5 Parameter Values:Fixed Cost per Order: k =\$10.006Annual Number of Items Demanded: A =
Jefferson College - QM - 670
Courseobjectives:1. To understand when and how to apply quantitative methodologicalanalysis to reach managerial decisions.2. To analytically solve problems involving quantitative business data.3. To determine the appropriate quantitative techniques n
Jefferson College - QM - 670
University of North AlabamaQM 670 Decision TheoryDr. BarrettRegression AnalysisGroup ThreeJoshua RayJ.W. HightowerJason BooiCourtney YoungAshley TaylorTopics of DiscussionHypothesisFactors of RegressionDataData AnalysisHypothesis Add in th
Jefferson College - QM - 670
Quarter12345678Machine Hrs.2000025000300002200021000180002400028000Power Cost2600038000425003700034000290003600040000SUMMARY OUTPUTRegression StatisticsMultiple R0.8933596724R Square0.7980915043Adjusted R Square0.76444008
Jefferson College - QM - 670
ABCDEFG1 SINGLE PERIOD INVENTORY MODEL - NEWSVENDOR PROBLEM2Wall Street Journal3 PROBLEM:4Parameter Values:5Cost per Item Procured: c =0.206Additional Cost for Each Leftover Item Held: h E =70.01Penalty for Each Item Short: pS =80.02
Jefferson College - QM - 670
ABCDEF1 SINGLE PERIOD INVENTORY MODEL - CHRISTMAS TREE PROBLEM2Noble Fir3 PROBLEM:4Parameter Values:5Mean of Demand Distribution: mu =6Stand. Deviation of Demand Distribution: sigma =7Cost per Item Procured: c =8Additional Cost for Each
Jefferson College - QM - 670
ABCDEFG1 MULTI-PERIOD EOQ MODEL (Backordering) - DISCRETE LEAD-TIME DEMAND2Printer Cartridges3 PROBLEM:4Parameter Values5Fixed Cost per Order: k =56Annual Demand Rate: A =15007Unit cost of Procuring an Item: c =1.58Annual Holding Co
Jefferson College - QM - 670
ABCDEF1 MULTI-PERIOD EOQ MODEL (Lost Sales) - DISCRETE LEAD-TIME DEMAND2Compact Discs3 PROBLEM:4Parameter Values5Fixed Cost per Order: k =6Annual Demand Rate: A =7Unit cost of Procuring an Item: c =8Annual Holding Cost per Dollar Value:
Jefferson College - QM - 670
ABCDEF1 MULTI-PERIOD EOQ MODEL (Backordering) - NORMAL LEAD-TIME DEMAND23 PROBLEM: Unleaded Gas at Oil Refinery45Parameter Values:6Mean of Demand Distribution: mu =7Stand. Deviation of Demand Distribution: sigma =8Fixed Cost per Order: k
Jefferson College - QM - 670
ABCDEF1 MULTI-PERIOD EOQ MODEL (Lost Sales) - NORMAL LEAD-TIME DEMAND23 PROBLEM: Roger's Sentinel Station45Parameter Values:6Mean of Demand Distribution: mu =7Stand. Deviation of Demand Distribution: sigma =8Fixed Cost per Order: k =9An
Jefferson College - QM - 670
Forecasting ExampleTo know the future is impossible. To predictthe future is easy. To accurately predict thefuture is what separates the Bill Gatess fromthe Barney Fifes.- Dr. StatsloveFoercasting Rules 1 and 21. DTDP Draw the darn picture! (This i
Jefferson College - QM - 670
Data for Samantha's Super Sectional SofasQuarter123456789101112131415161718192021222324%Defective7.316.197.446.617.337.436.747.356.8611.406.086.658.247.336.277.037.527.807.217.237.276.927.557.75Note: Thes
Jefferson College - QM - 670
Forecasting InventoryExampleTo know the future is impossible. To predictthe future is easy. To accurately predict thefuture is what separates the Bill Gatess fromthe Barney Fifes.- Dr. StatsloveExampleA firm is interested in determining how manyu
Jefferson College - QM - 670
Forecasting ProblemYou are the newly hired manager of Simpsons, Inc., a small company thatproduces nonwoven fabric. You are currently trying to determine the number of rolls offabric to produce during the first quarter for Burns &amp; Smithers. Your boss,
Jefferson College - QM - 670
Forecasting Thumbnail NotesPurpose: To use past data to predict future observations of business variables.Situation: We have an explanatory variable that is the given time period and some response variable thatneeds to be predicted for the future.Step
Jefferson College - QM - 670
Chapter 7My interest is in the future because I amgoing to spend the rest of my life there.Charles F. KetteringForecasting1Time-Series AnalysisA time series is numerical sequence ofvalues generated over regular time intervals.The classical time-s
Jefferson College - QM - 670
#N/A4598153.14.924.0157.517.49 56.100164.251-2.251 5.06700162.22518.7749 76.9988770.12251 4.87749 23.78990974.512251 2.487749 6.188895176.751225 5.2487749 27.54963881.475123 3.5248775 12.42476184.647512 -1.647512 2.714296683.164751 4.835
Jefferson College - QM - 670
Grocery Store Items1. Sara Lee Wheat Bread2. Pillsbury Cookie Dough3. Pampers Diapers4. Kraft Cheese Slices5. 12 Pack of Coca Cola6. Cool Ranch Doritos Chips7. Pop Tarts8. Welchs Grape Juice9. Digorno Pizza10. Texas Toast11. Grapes12. Honey Ha
Jefferson College - QM - 670
Frequently Purchased ItemsSara Lee Wheat BreadPillsbury Cookie DoughKraft Cheese Slices12 Pack of Coca ColaCool Ranch Doritos ChipsPop TartsWelchs Grape JuiceTexas ToastSuave ShampooKibbles and Bits Dog FoodChips Ahoy CookiesMayoBall Park Hot
Jefferson College - QM - 670
QM 670 Group Projects &amp; PresentationAs stated in the syllabus, you will complete two group projects and submit aPowerPoint presentation of the second project. All presentations will be scored by theclass members. The purpose of the assignments is twofo
Jefferson College - QM - 670
QM 670 Group Projects &amp; PresentationAs stated in the syllabus, you will complete two group projects and submit aPowerPoint presentation of the second project. All presentations will be scored by theclass members. The purpose of the assignments is twofo
Jefferson College - QM - 670
IndependentDemandInventoryManagementPowerPointsTypesofInventoryInventorycomesinmanyshapesandsizessuchasRawmaterialspurchaseditemsorextractedmaterialstransformedintocomponentsorproductsComponentspartsorsubassembliesusedinfinalproductWorkinproces
Jefferson College - QM - 670
Inventory Thumbnail NotesModels:Deterministic Models:1. Economic Order Quantity (EOQ) use when demand is known, constant,backorders/shortages are not allowed, and inventory usage is constant.Parameter Values:Fixed Cost per Order:k=Annual Number of
Jefferson College - QM - 670
QM 670 Inventory Homework: Jason BooiQuestion 2: (p.227)The current order quantity for Electric Powerbars is 100 bars. The order cost is \$10 per order, the holding cost is \$0.25 per box per year,and the annual demand is 2000 bars per yearOrder Quantit
Jefferson College - QM - 670
Please use the average household income, cost of living index, and population for each city from2009 - try your hardest to find 09. (Dr. Barrett's suggestion)Huntsville:Males: 86,494Females:93,159Median resident age:Alabama medianage:(48.1%)(51.
Jefferson College - QM - 670
More Sample InventoryProblemsNote: Refer to the InventoryThumbnail NotesEconomic Production QuantityExampleLambda Optics makes microscopic lenshousings. The housings can be produced at arate of 200,000 units/yr. Annual demand is100,000 units/yr.
Jefferson College - QM - 670
PopulationIndex179653604,13364516982.686.8135.7Median Income\$46,014\$37,331\$51,688Huntsville:Population in July 2009: 179,653. Population change since 2000: +13.5%Dec. 2009 cost of living index in Huntsville: 82.6 (low, U.S. average is 100)E
Jefferson College - QM - 670
1QM 670DECISION THEORYDr. Doug Barrett1.0 Decision Theory IntroductionDecision Making:1) Futureuncertainty2) Tradeoffs:Non-technicalBetter or best choiceNot necessarily the best choiceLinear program: unlikely to know all the coefficientsForecas
Jefferson College - QM - 670
QM 670 Regression ProblemsWe are using the following data to build a model to predict house prices.Price87155148290455122759810013614916521022514011510513810093Sq.Feet1400210024002900390023001300170016502250214018002170
Jefferson College - QM - 670
Dr. StatsloveOr: how I learned to stop worrying and love QMWelcome to QM 670! This is a brief introduction and syllabus addendum. Firstoff, I am J. Douglas (Doug) Barrett. Since we will be spending the next four months orso working together, I will te
Jefferson College - QM - 670
QM 670 Exam II1. ANF produces nonwoven fabric. An important measurement is the tensile strength,which is the strength of the fabric to avoid being torn apart. One customer hasspecified that the mean tensile strength must fall between 240 g/si (grams pe
Jefferson College - QM - 670
xam II: Jason Booi1. ANF produces nonwoven fabric. An important measurement is the tensile strength, which is the strength of the fabric to avoid being torn apart.One customer has specified that the mean tensile strength must fall between 240 g/si (gram
Jefferson College - QM - 670
QM 670 Inventory HomeworkDo problems 2, 4, 7, 8, and 11 on pp. 227-229.1. Beaver &amp; Thorne Inc. produces expensive decorative jewelry for prestigious upscaleManhattan department stores. Due to current capacity constraints, they produce anequal quantity
Jefferson College - QM - 670
1QM 670DECISION THEORYDr. Doug Barrett1.0 Decision Theory IntroductionDecision Making:1) Futureuncertainty2) Tradeoffs:Non-technicalBetter or best choiceNot necessarily the best choiceLinear program: unlikely to know all the coefficientsForecas
Jefferson College - QM - 670
Regression ExampleOr More Fun Than a Barrel ofTypical ValuesNote: Refer to the QM 670Regression Problems Handout Failure to do so could cause symptomssuch as headaches, confusion, ordrowsiness Please do not operate heavy machinerywhile doing QM h
Jefferson College - QM - 670
1. The management of Wheeler Company has decided to develop cost formulas for its major overhead activities.Quarter Machine Hrs.Power Cost1200002600022500038000330000425004220003700052100034000618000290007240003600082800040000Ma
Jefferson College - QM - 670
Quality HomeworkDo problems 2, 4, and 9 in Chapter 2 (pp 62-63)Do problems 1, 2, 3 in Chapter 11 (p. 441)
Jefferson College - QM - 670
Ashley WorleyQuality HomeworkChapter 2 Homework2.A.Upper Tolerance = 36Lower Tolerance = 24Mean = 30Standard Deviation = 4Actual Upper = 30+4*4 = 46Actual Lower = 30-4*4 = 14No, this company is not delivering six sigma quality because the upper
Jefferson College - QM - 670
SUMMARY OUTPUTRegression StatisticsMultiple R 0.6233156R Square 0.3885223Adjusted R 0.3179672SquareStandard Error2.2161226Observations30ANOVAdfRegressionResidualTotalInterceptAssetsSEPPESSMSFSignificance F3 81.132768 27.044256 5.506
Jefferson College - QM - 670
Linear Regression for Population1096.92 98.97 99.28 96.99 97.23T ot al PriceIndex.99Population50000Linear Regression for Index97.231-0.4652791-0.220293 0.63227310.7228947 -0.455224 -0.44863910000096Index Median Income.97T PricePo
Jefferson College - QM - 670
Regression and Correlation AnalysisSimple Linear Regression (SLR)Situation we wish to analyze the relationship between two continuous variables X andY). Y is the response variable, and is the variable we wish to predict. X is theexplanatory variable,
Berkeley - EE - 221A
EE 221a Homework 5 SolutionsFall 20071Problem 1. Since f (s) = es is an analytic function, the eigen-values of eA areei , i = 1, 2, . . . , n, where i s are eigen-values of A. So,ndet(eA ) =ei = 0i=1Problem 2. v Rn , Av N (A), that is, A2 v = , v