PPT-Random Variables Lesson

53 Binomial Random Variables 5 Determine whether or not a given scenario is a binomial setting Calculate probabilities involving a single value of a binomial random variable Make a histogram to display a binomial distribution and describe its shape. Value. Section . 7.4 (partially). Section Summary. Expected Value. Linearity of Expectations. Independent . Random . Variables. Expected Value. Definition. : The . expected value . (or . expectation . Expected Value. Airline overbooking. Pooling . blood . samples. Variance and Standard . Deviation . Independent Collections. Optimization. DECS 430-A. Business Analytics . I: Class 2. Random Variables. Signal Analysis. 02 Sep 2015. © A.R. Lowry . 2015. Last time:. Signal Analysis. . is a set of tools used to extract information. from. . sequences. . of. . random variables…. “. Review. ”. http://. rchsbowman.wordpress.com/2009/11/29. /. statistics-notes-%E2%80%93-properties-of-normal-distribution-2/. Chapter 23: Probability Density Functions. http://. divisbyzero.com/2009/12/02. /. an-applet-illustrating-a-continuous-nowhere-differentiable-function//. . .. . . Week 05 . Tues. . .. MAT135 Statistics. Random Variables. A random variable . . Random Variables. A random variable . . “varies” . . (not always the same). Random Variables. A random variable . 1. 5. Joint Probability Distributions. 5-1 Two or More Random Variables. 5-1.1 Joint Probability Distributions. 5-1.2 Marginal Probability Distributions. 5-1.3 Conditional Probability Distributions. Random Variables. Definition:. A rule that assigns one (and only one) numerical value to each simple event of an experiment; or. A function that assigns numerical values to the possible outcomes of an experiment.. In this lesson, we will:. Review the behavior of local variables and parameters. Introduce static variables. See how they work and how they can be applied. Generating unique identifiers. Applying specific algorithms. adding . constants to random variables, multiplying random variables by constants, and adding two random variables together. AP Statistics B. pp. 373-74. 1. Pp. 373-74 are just plain hard. I don’t like the way they are written. Explicitly . define them. Can give them starting values. Figures out type. Case sensitive. . var. x = 5; . (note: this is the ONLY use of =). Arrays. Collection of related . information. Referenced with index. Random Variables Expected Value Airline overbooking Pooling blood samples Variance and Standard Deviation Independent Collections Optimization DECS 430-A Business Analytics I: Class 2 Random Variables 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, Section 6.1. Discrete & Continuous Random Variables. After this section, you should be able to…. APPLY the concept of discrete random variables to a variety of statistical settings. CALCULATE and INTERPRET the mean (expected value) of a discrete random variable. 1. http://www.landers.co.uk/statistics-cartoons/. 5.1-5.2: Random Variables - Goals. Be able to define what a random variable is.. Be able to differentiate between discrete and continuous random variables..