PPT-Probability

Review Given N population X sample size P probability of successevent Q 1P probability of failurenon event Wanted Probability of X successes in population of N where member event occurs with probability P. 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. Vocab reminders. Genes are located at a particular. place on DNA (. locus. ). Focus on one locus.. Each partner in a homologous pair (one from mom, one from dad) has the same gene at that locus. The gene might vary, though—an . 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 . 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. 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.. 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.. 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.. 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 . Conditional Probability. Conditional Probability: . A probability where a certain prerequisite condition has already been met.. Conditional Probability Notation. The probability of Event A, given that Event B has already occurred, is expressed as P(A | B).. 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 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..