PPT-Joint, Marginal, and Conditional Distributions

Section 08 Joint distribution of X and Y defined over a twodimensional region Discrete Continuous X and Y may be independent or dependent   CDF of a joint distribution Discrete Continuous. 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. In relation to consumers!!!!!!. Marginal Utility. Marginal = Extra. Utility = Satisfaction. Diminishing marginal utility. Lets test:. If a consumer consumes 1 extra unit (marginal) of a good or service in succession what happens to their utility (satisfaction) after the consumption of that good.. 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. 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. Computer Science cpsc322, Lecture 26. (Textbook . Chpt. 6.1-2). Nov. , . 2013. Lecture Overview. Recap with Example. Marginalization. Conditional Probability. Chain Rule. Bayes. ' Rule. Marginal Independence. 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. “I revoke my will if [condition] occurs.”. 2. Implied conditional revocation. (Dependent Relative Revocation). Fact Pattern:. 1. Testator executed valid Will 1.. 2. Testator validly revoked Will 1.. © 2017 W.H. Freeman and Company. 1.1-1. When ordering vinyl replacement windows, the following variables are specified for each window. Which of these variables is . quantitative. ?. a. window style: double hung, casement, or awning. Marginal Revenue (MR): . Change. in the firm’s total revenue resulting from a . one unit change. in production.. Marginal Cost (MC): . Change. in the firm’s total cost resulting . from . a . one unit change . Richard Williams. rwilliam@ND.Edu. https://. www.nd.edu/~rwilliam. /. . University of Notre Dame. Original version presented at the Stata User Group Meetings, Chicago, July 14, 2011. Published . version available at . Diktys. Stratakis. 1. 2. Scott’s Shuffled Distributions. 3. ICOOL-MPI vs. ICOOL Classic. 2 minutes . (MPI) . vs. . 3 hours . (in my fast . laptop) vs. . 5 hours . in my cheap home laptop!. Shuffled and . .  . .  . .  . .  . .  . .  . Announcements. Assignments:. HW9 (written). Due Tue 4/2, 10 pm. Optional Probability (online). Midterm:. Mon 4/8, in-class. Course Feedback:. See Piazza post for mid-semester survey. 18. O AT 35 MEV/NUCLEON ON . 9. BE AND . 181. TA TARGETS. Erdemchimeg. Batchuluun. 1,2. , A.G Artukh. 1. , S.A Klygin. 1. , G.A Kononenko. 1. , . Yu.M. . Sereda. 1. , A.N. Vorontsov. 1. T.I, Mikhailova. Bayes nets encode joint distributions as product of conditional distributions on each variable:. P. (. X. 1. ,..,X. n. ) = . . i. . P. (. X. i. . | . Parents. (. X. i. )). P(B). true. false. 0.001.