PPT-S1 PROBABILITY

Laws of Probability Exhaustive events When a normal unbiased 6sided die is thrown the numbers 1 to 6 are possible These are the ONLY events possible This means these are EXHAUSTIVE as they cover ALL POSSIBLE OUTCOMES. A brief digression back to . joint probability: . i.e. . both events . O. . and. . H. occur. .  . Again, we can express joint probability in terms of their separate conditional and unconditional probabilities. 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. http://mikeess-trip.blogspot.com/2011/06/gambling.html. 1. Uses of Probability. Gambling. Business. Product preferences of consumers. Rate of returns on investments. Engineering. Defective parts. Physical Sciences. Experimental probability. : . Probability based on a collection of data.. Will have a table of results or data from the experiment(s)!. What is the difference between . theoretical probability. and . 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. 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.. 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.. 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.. 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.. 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 .