PPT-Chapter 4. Discrete Probability Distributions

Sections 47 48 Poisson and Hypergeometric Distributions Jiaping Wang Department of Mathematical Science 03042013 Monday Outline Poisson Probability Function Poisson Mean and Variance. Probability Distributions . and Data Modeling. Business Analytics: Methods, Models, . and Decisions. , 1. st. edition. James R. Evans. 5-. 1. Copyright © 2013 Pearson Education, Inc. publishing as Prentice Hall. AS91586 Apply probability distributions in solving problems. NZC level 8. Investigate situations that involve elements of chance. calculating and interpreting expected values and standard deviations of discrete random variables. 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 . Continuous distributions. Sample size 24. Guess the mean and standard deviation. Dot plot sample size 49. Draw the population distribution you expect. Sample size 93. Sample size 476. Sample size 948. 1. 3. Discrete Random Variables and Probability Distributions. 3-1 Discrete Random Variables. 3-2 Probability Distributions and Probability Mass Functions. 3-3 Cumulative Distribution Functions. 3-4 Mean and Variance of a Discrete Random Variable. A Brief Introduction. Random Variables. Random Variable (RV): A numeric outcome that results from an experiment. For each element of an experiment’s sample space, the random variable can take on exactly one value. Applied Statistics and Probability for Engineers. Sixth Edition. Douglas C. Montgomery George C. . Runger. Chapter 5 Title and Outline. 2. 5. Joint Probability Distributions. 5-1 Two or More Random Variables. Probability Terminology. Classical Interpretation. : Notion of probability based on equal likelihood of individual possibilities (coin toss has 1/2 chance of Heads, card draw has 4/52 chance of an Ace). Origins in games of chance.. St. . Edward’s. University. .. .. .. .. .. .. .. .. .. .. .. Chapter 5. Discrete Probability Distributions. .10. .20. .30. .40. 0 . . 1 . . 2 3 4. Random Variables. http://www.answers.com/topic/binomial-distribution. Chapter 13: Bernoulli Random Variables. http://www.boost.org/doc/libs/1_42_0/libs/math/doc/sf_and_dist/html. /. math_toolkit. /. dist. /. dist_ref. Section 5-3 – Normal Distributions: Finding Values. A. We have learned how to calculate the probability given an . x. -value or a . z. -score. . In this lesson, we will explore how to find an . . 3.1 - Random Variables. 3.2 - Probability Distributions for Discrete. Random Variables . 3.3 - Expected Values. 3.4 - . The Binomial Probability Distribution. 3.5 - Hypergeometric and Negative. 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). . 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..