PPT-Probability distribution functions

Normal distribution Lognormal distribution Mean median and mode Tails Extreme value distributions Normal Gaussian distribution P robability density function PDF What does figure tell about the cumulative distribution function . 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. 5.1.1 Random Variables and Their Distributions. A random variable is a quantity that (prior to observation) can be thought of as dependent on chance phenomena. . . Toss a coin 10 times. X=# of heads. Objectives:. By the end of this section, I will be. able to…. Explain what constitutes a binomial experiment. . Compute probabilities using the binomial probability formula.. Find probabilities using the binomial tables.. Stephen Mansour, . PhD. University of Scranton and The Carlisle Group. Dyalog. ’14 . Conference, . Eastbourne. , UK. M. any statistical software packages out there: Minitab, R, Excel, SPSS. Excel has about 87 statistical functions. 6 of them involve the t distribution alone: . 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. Distributions. 6.1 Continuous Uniform Distribution. One of the simplest continuous distributions in all of statistics is the . continuous. uniform distribution. . This distribution is characterized by a density function. 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.. 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.. What we learned last class…. We are not good at recognizing/dealing with randomness. Our “random” coin flip results weren’t streaky enough.. If B/G results behave like independent coin flips, we know how many families to EXPECT with 0,1,2,3,4 girls.. March 4, 2015. First things first. The Exam. Due to Monday’s class cancellation. Today’s lecture on the Normal Distribution . will not. be covered on the Midterm. However, the previous lecture, on the Binomial Distribution, . 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.. 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 In this class we will review . how statistics are used to . summarize data, special probability distributions, . their . use in simple applications using Frequentist and Bayesian . methods, and Monte Carlo techniques. It is also known as the Gaussian distribution and the bell curve. .. The general form of its probability density function is-. Normal Distribution in . Statistics. The normal distribution is the most important probability distribution in statistics because it fits many natural phenomena. .