PPT-Probability 2.0

Independent Events Events can be Independent meaning each event is not affected by any other events Example Tossing a coin Each toss of a coin is a perfect isolated thing What it did in the past will not affect the current toss. With an Emphasis on Contingency . Tables. Students in PSYC 2101. Skip to Slide . # 7. . Random Variable. A . random variable. is real valued function defined on a sample space. .. The . sample space. Assigning Probabilities and Probability Relationships. Chapter 4. BA 201. Assigning Probabilities. Assigning Probabilities. Basic Requirements for Assigning Probabilities. 1. The probability assigned to each experimental. and Independence . in the Common Core. CMC Annual Conference. Palm Springs, CA. November, 2013.   . Josh Tabor. Canyon del Oro High School. joshtabor@hotmail.com. From the . Common Core State Standards. Mat 271E. Yard. Doç. Dr. Tarkan Erdik. Probability Distributions. Uniform and Normal Distributions- Week 7. 1. Probability Distributions. 2. It has been observed that . certain functions . F(x). and . Sections 4.7, 4.8: Poisson and . Hypergeometric. Distributions. Jiaping. Wang. Department of Mathematical Science . 03/04/2013, Monday. Outline. Poisson: Probability Function. . Poisson: Mean and Variance. Unit 4. Introduction. Many decisions in business, insurance, and other real-life situations are made by assigning probabilities to all possible outcomes pertaining to the situation and then evaluating the results. For example, a saleswomen can compute the probability that she will make 0,1,2 or 3 or more sales in a single day. An insurance company might be able to assign probabilities to the number of vehicles a family owns. Once these probabilities are assigned, statistics such as mean, variance and standard deviations can be computed for these events. With these statistics, various decisions can be made.. Coins game. Toss 3 coins. You win if . at least two . come out heads. S. = { . HHH. , . HHT. , . HTH. , . HTT. , . T. HH. , . T. HT. , . T. TH. , . T. TT. }. equally likely outcomes. W. = { . HHH. Joyeeta Dutta-Moscato. May 24, 2016. There are three kinds of lies: lies, damned lies and statistics. . - Mark Twain, attributed to Disraeli. Sample vs population. Central tendency: Mean, median, mode. 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.. 4. Introduction. (slide 1 of 3). A key . aspect of solving real business problems is dealing appropriately with uncertainty.. This involves recognizing explicitly that uncertainty exists and using quantitative methods to model uncertainty.. Slide . 2. Probability - Terminology. Events are the . number. of possible outcome of a phenomenon such as the roll of a die or a fillip of a coin.. “trials” are a coin flip or die roll. Slide . Probability and Probability Distribution Dr Manoj Kumar Bhambu GCCBA-42, Chandigarh M- +91-988-823-7733 mkbhambu@hotmail.com Probability and Probability Distribution: Definitions- Probability Rules –Application of Probability calculus. 1 ≥ . Pr. (h) ≥ 0. If e deductively implies h, then Pr(h|e) = 1. .. (disjunction rule) If h and g are mutually exclusive, then . Pr. (h or g) = . Pr. (h) + . Pr. (g). (disjunction rule) If h and g are . 4. Compute the number of combinations of . n. individuals taken . k. at a time.. Use . combinations to calculate probabilities.. Use . the multiplication counting principle and combinations to calculate probabilities..