PPT-Chapter 4: Probability: The Study of

Chapter 4 Probability The Study of Randomness Lecture Presentation Slides Macmillan Learning 2017 Chapter 4 Probability The Study of Randomness 41 Randomness 42 Probability Models 43 Random Variables. 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.. Section 2.4. Counting Rules Useful in Probability. Jiaping. Wang. Department of Mathematical Science . 01/23/2013, Wednesday. Outline. Fundamental Principle of Counting. . . Permutations. . Section 5.1. An event is the set of possible outcomes. Probability is between 0 and 1. The event A has a complement, the event not A. Together these two probabilities sum 1.. . ex. At least one and none are complements. Section 2.3. Definition of Probability. Jiaping. Wang. Department of Mathematical Science . 01/16/2013, Wednesday. Outline. . Introduction. . . Definition of Probability. . . Inclusive-Exclusive Principle. 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. 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 . 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.. 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. 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 . 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 . Chapter Summary. Introduction to Discrete Probability. Probability Theory. Bayes. ’ Theorem. An Introduction to Discrete Probability. Section . 7.1. Section Summary. Finite Probability. Probabilities of Complements and Unions of Events. A value between zero and one that describe the relative possibility(change or likelihood) an event occurs.. The MEF announces that in 2012 the change Cambodia economic growth rate is equal to 7% is 80%.. Chapter 4: Probability: The Study of Randomness Lecture Presentation Slides Macmillan Learning © 2017 Chapter 4 Probability: The Study of Randomness 4.1 Randomness 4.2 Probability Models 4.3 Random Variables