PPT-Part 2: Named Discrete Random Variables

httpwwwanswerscomtopicbinomialdistribution Chapter 13 Bernoulli Random Variables httpwwwboostorgdoclibs1420libsmathdocsfanddisthtml mathtoolkit dist distref. 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 QSCI 381 – Lecture 12. (Larson and Farber, Sect 4.1). Learning objectives. Become comfortable with variable definitions. Create and use probability distributions. Random Variables-I. A . http://www-users.york.ac.uk/~pml1/bayes/cartoons/cartoon08.jpg. 1. Comparison of Named Distributions. discrete. continuous. Bernoulli,. Binomial, Geometric, Negative Binomial, Poisson, Hypergeometric, Discrete Uniform. Lecture 4 – Part 2. M. Pawan Kumar. pawan.kumar@ecp.fr. Finite set . Σ. called alphabet of size ≥ 2. {0,1}. {. a,b,c,d,e. ,…,. x,y,z. }. Set . Σ. * of all finite length strings (called words). 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.. http://www.answers.com/topic/binomial-distribution. Chapter 18: Poisson Random Variables. http://. www.boost.org/doc/libs/1_35_0/libs/math/doc/sf_and_dist/html. /. math_toolkit. /. dist. /. dist_ref. 1. Matt Gormley. Lecture 2. August 31, 2016. School of Computer Science. Readings:. Mitchell Ch. 1, 2, 6.1 – 6.3. Murphy Ch. 2. Bishop Ch. 1 - 2. 10-601 Introduction to Machine Learning. Reminders. 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.. . .. . . 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 . 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.. Random variable: A variable whose value is determined by the outcome of a random experiment is called a random variable. Random variable is usually denoted by X. A random variable may be discrete or 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. 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.. 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..