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Course: ESE 502, Fall 2011
School: UPenn
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UPenn - ESE - 502
REGRESSION EXAMPLE Given data points xi = i , i =1,.,20 Consider the regression modelYi = 0 + 1 xi + i , i = 1,.,20 u1i = i1 + ui, i =1, i = 2,.,20ui iid N (0, 2 ) , i = 1,.,20:with parameters 0 = 1 , 1 = 0.8 , = 2302520151050-5-1002
UPenn - ESE - 502
REGRESSION SIMULATIONSY = 0 + 1 x1 + 2 x2 + u, [ 0 = 1, 1 = .04, 2 = .08]where u N (0, ) with :ij = s (hij | r , a, s ), hij = dist (i, j ),[r = 5, a = 0, s = 1]Simulation Summary (average values for 100 samples):GLS Est GLS Std Errconst 0.92840.48
UPenn - ESE - 502
T0T0T1T0T1T2 22 2 2T0T1 2T2T3 32 23 3 23 3 3T0T1 2T2 3T3T4 42 23 34 4 23 36 4 34 4 4
UPenn - ESE - 502
EXAMPLES OF SMOOTHERS FOR SPATIAL INTERPOLATION IN GEOSTATISTICAL ANALYSTESE 502 Tony E. SmithLocal Polynomial FitRadial Basis FitSpline Function FitOrdinary Krige FitLOCAL LINEAR POLYNOMIAL FITRADIAL BASIS FUNCTIONSGiven data ( si , yi ) , i = 1,
UPenn - ESE - 502
Spatial Autocorrelation Problem One-Dimensional ExampleAssume x values increasing along a roadwayTRUE TRENDy Correlated ErrorsxTRUE TRENDy REGRESSION LINEx
UPenn - ESE - 502
SPATIAL DIFFUSIONANALYSISExample Application Areas Diffusion of Information Diffusion of Toxic Wastes Spread of Infectious DiseasesProduct Adoption ExampleTony E. Smith and Sanyoung Songhttp:/www.seas.upenn.edu~tesmith Basic Model Steady State A
UPenn - ESE - 502
VECTOR COSINESAND ORTHOGONALITYxyy2min x y = ( x y )( x y )= xx 2 xy + 2 yy x y0=2= 2 xy + 2 yyxy xy ==2yyyxycos( ) =yx=yyx=xy yy2x=xyyx
UPenn - ESE - 502
MATLAB 5.0 MAT-file, Platform: PCWIN, Created on: Sat Feb 12 16:11:50 2005#IM#c##hgS_050200#7#type#handle#properties#children#special#@##f#i#g#u#r#e#0##Color#Colormap#InvertHardcopy#PaperPosition#Position#ResizeFcn#ApplicationData#DefaultaxesCreate
UPenn - ESE - 502
USC - BUAD - 310
M ul tiple Regression ProjectBUAD 31010:00 T, ThProfessor Gabrys4/28/11Team Members:Nicholaus JohnsonBrett KanA aron KimEugene KimJason K imJeremy K lifDavid KoRoy Kwon1 a) Examine the var iables and thei r relationships to each other:Profi
USC - BUAD - 310
M ul tiple Regression ProjectBUAD 31010:00 T, ThProfessor Gabrys4/28/11Team Members:Nicholaus JohnsonBrett KanA aron KimEugene KimJason K imJeremy K lifDavid KoRoy Kwon1 a)E xamine the var iables and thei r relationships to each other:Prof
USC - BUAD - 310
Jeremy K lifBUAD 310ID: 9128653432STATISTICS PROJECT1)a)Commission has no pattern of skeweness. Profit is very roughly normal butleft skewed. Area is heavily r ight skewed because the peaks are on the leftand it is unimodal. Outlet is roughly norm
USC - BUAD - 310
1)a)Pagecost and circulation seem to be pretty r ight skewed. Percentage of male and mediani ncome seem to be bimodal and do not really have any pattern of skewness.b) y=bo + b1x1 + b2x2 + b3x3 + EpsilononB) Page cost and circulation seem to have a m
USC - BUAD - 310
Nicholaus Johnson1. Examine the variables and their relationships to each other:a)Profit is roughly normal with no pattern of skeweness (peaks are in the middle of thegraph). Area is unimodal (has one peak) and right skewed (peak is to the left of the
USC - BUAD - 310
ProjectDue Friday, April 29The marketing managers of an office products company have some difficulty inevaluating the field sales representatives performance. The representatives travel among theoutlets that carry companys products, create displays, t
USC - BUAD - 310
DIST1234567891011121314151617181920212223242526272829303132333435363738394041424344PROFIT AREAPOPNOUTLETS COMMIS101116.963.88213113187.313.14158115567.813.77203115217.314.59170197919.84
USC - BUAD - 310
Nicholas HuangProjectBUAD-310, Section: 14880Instructor: Robertas GabrysApril 29, 2011BUAD-310Project1. Examine the variables and their relationships to each other:a. First look at how each variable behaves on its own by creating histograms ofeac
USC - BUAD - 310
USC - BUAD - 310
Use the following to answer question 1.The researchers conducting this study wish to estimate the winnings when the averagenumber of putts per hole is 1.75. The following results were obtained from software.Predicted winningsStandard error95.0% C.I.
USC - BUAD - 310
BUAD 310: Final ExamFirst name: . Last name:.1. You are doing a one sided, greater than, hypothesis test for the population proportion using a sample of 25, and youget a test statistic of 1.7. This means:A)B)C)D)E)you cannot reject the null hypot
USC - BUAD - 310
1234567891011121314151617181920212223242526272829303132333435363738394041424344454647CBAEDEEABDCBDBDEBBDAAACBBBBCABABABAAAAABABABBAA48 A49 A50 A
USC - BUAD - 310
Solutions toMix and Matchand TRUE/FALSEproblems from the textbook
USC - BUAD - 310
BUAD 310: Quiz 2First name: . Last name:.Use the following to answer questions 1 and 2:A survey taken at several large corporations involved 1000 randomly selected management personnel. For each personsurveyed, it was determined whether or not they ha
USC - BUAD - 310
BUAD 310: Quiz 2 KEYUse the following to answer questions 1 and 2:A survey taken at several large corporations involved 1000 randomly selected management personnel. For each personsurveyed, it was determined whether or not they had obtained an MBA degr
USC - BUAD - 310
USC - BUAD - 310
BUAD 310: Quiz 3First name: . Last name:.Use the following to answer questions 1 and 2:An assembly plant orders a large shipment of electronic circuits each month. The supplier claims that the population proportionof defective circuits is =.04. When a
USC - BUAD - 310
BUAD 310: Quiz 3 KEYFirst name: . Last name:.Use the following to answer questions 1 and 2:An assembly plant orders a large shipment of electronic circuits each month. The supplier claims that the population proportionof defective circuits is =.04. Wh
USC - BUAD - 310
MultipleLinearRegressionBUAD310AppliedBusinessStatisticsMultipleLinearRegressionBasicMultipleRegressionModelMeasuresofFitInferenceMulticollinearityBUAD3102Example:SwissFertilityRatesFertilityindex,Switzerland,1988;MostellerandTukey,pages550551
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.Estimation with confidenceMain idea:instead of seeking a single value thatwe designate to be the estimate of theunknown population parameter ofinterest (i.e. X), we can attempt tospecify an interval of values t
USC - BUAD - 310
Simple Linear RegressionSimple Linear RegressionSimple Linear Regression Model LeastSquares Point Estimates Model Assumptions Variation Coefficient of DeterminationInference F-Test Coefficientt-testsCIs and Prediction Intervals (PI)BUAD 3102
USC - BUAD - 310
Chapter 1IntroductionCopyright 2011 Pearson Education, Inc.1.1 What is Statistics?Some Basic IdeasStatistics as a disciplineQuestions we can answer with statisticsVariation, patterns and models3 of 18Copyright 2011 Pearson Education, Inc.1.1 Wha
USC - BUAD - 310
Chapter 2DataCopyright 2011 Pearson Education, Inc.2.1 Data TablesSome Basic IdeasData are a collection of numbers, labels, orsymbols with contextA data table is a rectangular arrangement of datawith rows and columnsObservations or cases form the
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.3.1 Looking At DataWhich hosts send the most visitors toAmazons Web site?Data set consists of 188,996 visitsHost is a categorical variableTo answer this question we must describe thevariation in HostCopyright
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.6.1 ScatterplotsIs household natural gas consumptionassociated with climate?Annual household natural gas consumptionmeasured in thousands of cubic feet (MCF)Climate as measured by the National WeatherService us
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.7.1 From Data to ProbabilityIn a call center, what is the probability that anagent answers an easy call?An easy call can be handled by a first-tier agent;a hard call needs further assistanceTwo possible outcomes
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.8.1 From Tables to ProbabilityHow does education affect income?Percentages computed within rows or columns ofa contingency table correspond to conditionalprobabilitiesConditional probabilities allow us to answer
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.9.1 Random VariablesWill the price of a stock go up or down?Need language to describe processes that showrandom behavior (such as stock returns)Random variables are the main components ofthis languageCopyright
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.10.1 Portfolios and Random VariablesHow should money be allocated amongseveral stocks that form a portfolio?Need to manipulate several random variables atonce to understand portfoliosSince stocks tend to rise an
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.12.1 Normal Random VariableBlack Monday (October, 1987) promptedinvestors to consider insurance againstanother accident in the stock market.How much should an investor expect topay for this insurance?Insurance
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.When the discussion turns out to the prosand cons of wearing automobile seat belts,Herman always brings up the case of afriend who survived an accident because hewas not wearing a seat belt. The friend wasthrown
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.The U.S. justice systemand hypothesis testingAn accused person is presumed innocent untilproven guilty.The burden of proof is one on the prosecution toshow that the accused is guilty.Thus the hypothesis are:Ho
USC - BUAD - 310
Copyright 2011 Pearson Education, Inc.18.1 Data for ComparisonsA fitness chain is considering licensing aproprietary diet at a cost of \$200,000. Is itmore effective than the conventional freegovernment recommended food pyramid?Use inferential statis
USC - BUAD - 311
categorical: ordinal or nominalnumerical: interval (no absolute zero) and ratioslikert scale: strongly agree disagreerecoding: bulding a new variable from anotheraggregate: reduce rows by summing valuestime series: data recorded over timetimeplot: g
USC - BUAD - 311
1)You are doing a one sided, greater than, hypothesis test for the population proportion using a sample of 25, and you get a test statistic of 1.7.: you canreject the null hypothesis at the 5% significance level, but not at the 2.5% level2.Determine the
USC - BUAD - 311
Decision tree: square: decision and circle is an event + first branch(different decision) and second branch(what happens in each case)In decision trees: cost willing to pay= difference between different decisions starting with the optimal oneCapacity co
USC - BUAD - 311
LP: must be limited resources + objective(maximize or minimize) + linearity + homogeneity + divisibilityGraphin: formulate mathematical equations then plot constraint equations then determine the area of feasibility then plot the objective function then
USC - BUAD - 311
square: activity / upside downtriangle: storage / diamond: decision / arrow: flowMTO: fast but bad quality and many may not be soldrisk pooling effect: by aggregating individual processes the variability is decreased and better perf can beachievedbott
USC - BUAD - 311
E OQ Model: Total cost= DC +(D/Q)S +(Q/2)H =annual purchase cost + annual ordering cost+ annualholding costtotal holding cost= average inventory * annual holding cost= q/2 * HTotal set up cost= annual ordering cost= Demand/quantity * set up cost each t
USC - BUAD - 311
LITTLEFIELD GAME #2 WRITE-UPPrior to the start of Littlefield game #2, our team analyzed our process specifically thequeues, the machine utilizations and the Work In Process. We came to the conclusion thatwe should increase the reorder point to 50 but
USC - BUAD - 311
Littlefield GamesBUAD311 Operations ManagementSpring 2011Please form a group of 5 or less students. We will be playing two games. The first game starts at 7:00pmon Sunday, February 27. The second game starts at 7:00pm on Sunday, April 17.[Game Code]
USC - BUAD - 311
Root Beer GameBUAD311 Operations ManagementSpring 2011Amy WardSection 14905You need one laptop per group in Session 26 on 4/14. Flash 9 or later is required. You must haveregistered online by class Tuesday on 4/12.[Registration]You need to purchas
USC - BUAD - 311
LITTLEFIELD GAME OBSERVATIONBefore the Littlefield Game began, our team analyzed the current working system of thegame, examining the queues of each machine. After thorough observations and calculations, werealized that Machine one was the bottleneck,
USC - BUAD - 311
Homework #3Decision Analysis and Revenue ManagementBUAD311- Operations ManagementSpring 2011Amy WardDue in-class on April 7Homework 3 has a maximum of 50 points. There are 3 questions. Students can discusshomework questions with each other, with TA
USC - BUAD - 311
Homework #4EOQ and NewsvendorBUAD311- Operations ManagementSpring 2011Amy WardDue in-class on April 14Homework 4 has a maximum of 50 points. There are 4 questions. Students can discusshomework questions with each other, with TAs, or with the instru
USC - BUAD - 311
1. What makes Zara different from other specialty apparel retailers?First of all, Zara uses a different distribution than other specialty apparel retailers. It iscentralized and they make shipments twice a week so that the clothes are in stores in 24to
USC - BUAD - 311
Name_Student ID_Section_BUAD-311 Operations ManagementIllustrative Final Exam1 SolutionsOpen Book, Open Notes,No LaptopsState all your assumptions clearlyBullet Points are preferred to long sentencesAll questions must be answeredMake sure that y
USC - BUAD - 311
Name_Student ID_Section_BUAD-311 Operations ManagementIllustrative Final Exam1Open Book, Open Notes,No LaptopsState all your assumptions clearlyBullet Points are preferred to long sentencesAll questions must be answeredMake sure that you have 13
USC - BUAD - 311
Illustrative Final Exam1SolutionsBUAD311 Operations ManagementSection A: Multiple Choices [4 pts each]1.To generate in Excel a uniformly distributed random variable between 5 and 10you need to use the following:a) 5*RAND()b) 5+RAND()c) 10+5*RAND(
USC - BUAD - 311
Name: (please print)Illustrative Final Exam1BUAD311 Operations Management1 hour and 50 minutesAll together the exam has a maximum of 100 points.There are 7 pages including this page.This is an open-book, open-notes exam. You may use a simple calcula
USC - BUAD - 311
Name: (please print)Illustrative Final Exam1SolutionsBUAD311 Operations Management1 hour and 45 minutesAll together the exam has a maximum of 100 points.There are ? pages including this page.This is an open-book, open-notes exam. You may use a simp
USC - BUAD - 311
Name: (please print)Illustrative Final Exam1BUAD311 Operations Management1 hour and 45 minutesAll together the exam has a maximum of 100 points.There are 9 pages including this page.This is an open-book, open-notes exam. You may use a simple calcula