PPT-Probability Density Functions

Jake Blanchard Spring 2010 Uncertainty Analysis for Engineers 1 Random Variables We will spend the rest of the semester dealing with random variables A random variable is a function defined on a particular sample space. Continuous Random Variables. Dr J Frost (jfrost@tiffin.kingston.sch.uk). www.drfrostmaths.com . Last modified: . 1. st. October 2015. Discrete vs Continuous Distributions. You all know the distinction between discrete and continuous variables:. 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. . Chapter 1 - Overview and Descriptive Statistics. . Chapter 2 - Probability. . Chapter 3 - Discrete Random Variables and Probability Distributions. Chapter 4 - Continuous Random Variables and Probability Distributions. 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. Ha Le and Nikolaos Sarafianos. COSC 7362 – Advanced Machine Learning. Professor: Dr. Christoph F. . Eick. 1. Contents. Introduction. Dataset. Parametric Methods. Non-Parametric Methods. Evaluation. 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. 3.1 . The Concept of Probability. 3.2 . Sample Spaces and Events. 3.3 . Some Elementary Probability Rules. 3.4 . Conditional Probability and Independence. 3.5 . Bayes’ Theorem. 3-. 2. Probability Concepts. Probability is used all of the time in real life. Gambling . Sports. Weather. Insurance. Medical Decisions. Standardized Tests. And others. Definition of Probability. “The . likelihood of something . 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 . Sixth Edition. Douglas C. Montgomery George C. . Runger. Chapter 2 Title and Outline. 2. 2. Probability. 2-1 Sample Spaces and Events . 2-1.1 Random Experiments. 2-1.2 Sample Spaces . Sixth Edition. Douglas C. Montgomery George C. . Runger. Chapter 2 Title and Outline. 2. 2. Probability. 2-1 Sample Spaces and Events . 2-1.1 Random Experiments. 2-1.2 Sample Spaces . 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 . http://www.alexfb.com/cgi-bin/twiki/view/PtPhysics/WebHome. Probability for two continuous . r.v. .. http://tutorial.math.lamar.edu/Classes/CalcIII/DoubleIntegrals.aspx. Example 1 (class). A man invites his fiancée to a fine hotel for a Sunday brunch. They decide to meet in the lobby of the hotel between 11:30 am and 12 noon. If they arrive a random times during this period, what is the probability that they will meet within 10 minutes? (Hint: do this geometrically).