PPT-Random Variables Expected Value

Random Variables Expected Value Airline overbooking Pooling blood samples Variance and Standard Deviation Independent Collections Optimization DECS 430A Business Analytics I Class 2 Random Variables. RANDOM VARIABLES Definition usually denoted as X or Y or even Z and it is th e numerical outcome of a random process Example random process The number of heads in 10 tosses of a coin Example The number 5 rating Value. Section . 7.4 (partially). Section Summary. Expected Value. Linearity of Expectations. Independent . Random . Variables. Expected Value. Definition. : The . expected value . (or . expectation . CS648. . Lecture 22. Chebyshev. . Inequality. Method of . Bounded Difference. 1. Chernoff. . Bound . Theorem . : Suppose . be . independent . Bernoulli. random variables with parameters . , that is, . Expected Value. Airline overbooking. Pooling . blood . samples. Variance and Standard . Deviation . Independent Collections. Optimization. DECS 430-A. Business Analytics . I: Class 2. Random Variables. First center (expected value). Now - spread. 4.2 (cont.) Standard Deviation of a Discrete Random Variable. Measures how “spread out” the random variable is. Summarizing data and probability. Data. Stern School of Business. IOMS Department . Department of Economics. Statistical Inference and Regression Analysis: . Stat-GB.3302.30, Stat-UB.0015.01. Part . 2 – A. Expectations of Random Variables. Gage Repeatability and . Repproducibility. . Experiment for Measuring Drill Holes in Wood Parts. Source: M-H. C. Li and A. Al-. Refaie. (2008). “Improving Wooden Parts’ Quality by Adopting DMAIC Procedure,” . Expectation And Variance of Random Variables Farrokh Alemi Ph.D. Random Variable Probability of Random Variable Expected Value Expected Value Dental Service Dental Service Dental Service Dental Service HW 3 Statistics  Suppose that X is a discrete random variable whose distribution is Value of X: x 1 x 2 x 3 … x k Probablily: p 1 p 2 p 3 … p k  To find the mean (also called the expected P(X=1) = P({3}) =1/6 X=5 P(X Let X = your earnings X = 100-1 = 99 X = -1 P(X=99) = 1/(12 3) = 1/220 P(X=-1) = 1-1/220 = 219/220 E(X) = 100*1/220 Let X be a random variable assuming the values x1, PX1 P3 1/6 X5 PXLet X your earnings X 100-1 99 X -1 PX99 1/12 3 1/220 PX-1 1-1/220 219/220 EX 1001/220Let X be a random variable assuming the values x1 x2 x3 with corresponding probabi CHAPTER 4242MathematicalExpectationDefinition41IfXisarandomvariablethentheexpectedvalueforXisdefinedasNoteExpectedvalueofXmeanforXthefirstmomentforX3Definition42IfwisafunctionofXandtheprobabilityfunct Objective. : . Use experimental and theoretical distributions to make judgments about . the . likelihood of various outcomes in uncertain . situations. CHS Statistics. Decide if the following random variable x is discrete(D) or continuous(C). . Section 6.1. Discrete and Continuous. Random Variables. Discrete and Continuous Random Variables. USE the probability distribution of a discrete random variable to CALCULATE the probability of an event..