1. Summary -1 Chapters 2-6 of DeCoursey

2. Basic Probability (Chapter 2, W.J.Decoursey, 2003) Objectives: -Define probability and its relationship to relative frequency of an event. -Learn the basic rules of combining probabilities. -Understand the concepts of mutually exclusive / not mutually exclusive and independent / not independent events. -Apply these concepts to solve sample problems.

3. Basic Probability Basic Rules of Combining Probability: -Addition Rule: Pr [event A] = C, Pr [event B] = D, what is the probability of Pr [event A or event B] ? Equals C+D? Case one: Mutually exclusive events: if one event occurs, other events can not occur. There is no overlap. The probability of occurrence of one or another of more than one event is the sum of the probabilities of the separate events. Example one. ABVenn Diagram Pr [ A U B ] = Pr [A] +Pr [B] Pr [ A U B ] = Pr [occurrence of A or B or Both]

4. Basic Probability Basic Rules of Combining Probability: -Addition Rule: Case two: Not mutually exclusive events: there can be overlap between them. The probability of overlap must be subtracted from the sum of probabilities of the separate events. A B A∩BA∩B Pr [ A U B ] = Pr [occurrence of A or B or Both] Pr [ A U B ] = Pr [A] +Pr [B] – Pr [A ∩ B] Pr [A ∩ B] = Pr [occurrence of both A and B] Venn Diagram

5. Basic Probability Basic Rules of Combining Probability: -Multiplication Rule: a. The basic idea for calculating the number of choices: - There are n 1 possible results from one operation. - For each of these, there are n 2 possible results from a second operation. - Then here are (n 1 Xn 2 ) possible outcomes of the two operations together.

6. Basic Probability Basic Rules of Combining Probability: -Multiplication Rule: b. Independent events The occurrence of one event does not affect the probability of the occurrence of another event. The probability of the individual events are multiplied to give the probability of them occurring together. Consider 2 events, A and B. Then the probability of A and B occurring together is Pr [A] * Pr [B] Note the use of logical AND

7. Basic Probability Basic Rules of Combining Probability: -Multiplication Rule: c. Not-independent events The occurrence of one event affects the probability of the occurrence of another event. The probability of the affected event is called the conditional probability since it is conditional upon the first event taking place. The multiplication rule then becomes for A and B occurring together Pr [A ∩ B]=Pr [A] * Pr [B|A] Pr [B|A] : conditional probability of B. (examples in class)

8. Basic Probability Summary of Combining Rule When doing combined probability problems, ask yourself: 1.Does the problem ask the logical OR or the logical AND? 2.If OR, ask your self are the events mutually exclusive or not? If yes, Pr [ A U B ] = Pr [A] +Pr [B], other wise Pr [ A U B ] = Pr [A] +Pr [B] – Pr [A ∩ B] 3.If AND, use the multiplication rule and remember conditional probability. A probability tree may be helpful. 4.Fault Tree Analysis

9. Basic Probability Permutations and Combinations: -Permutations: a. A total of n distinguishable items to be arranged. R items are chosen at a time (r ≤ n). The number of permutations of n items chosen r at a time is written n P r.

10. Basic Probability Permutations and Combinations: -Permutations: b. To calculate the number of permutations into class. A total of n items to be placed. n 1 items are the same of one class, n 2 are the same of the second class and n 3 are the same as a third class. n 1 +n 2 +n 3 =n The number of permutations of n items taken n at a time:

11. Basic Probability Permutations and Combinations: -Combinations: c. Similar to Permutations but taking no account of order. The number of combinations of n items taken r at a time:

12. Descriptive Statistics Objectives: (Chapter 3, Decoursey) - To understand the definition of mean, median, variance, standard deviation, mean absolute deviation and coefficient variation and calculate these quantities. - To calculate some of these quantities using the statistical functions of Excel.

13. Descriptive Statistics

14. Probability Distributions, Discrete Random Variables Objectives: (Chapter 5, DeCoursey) - To define a probability function, cumulative probability, probability distribution function and cumulative distribution functions. - To define expectation and variance of a random variable. - To determine probabilities by using Binomial Distribution.

15. Probability Distributions, Discrete Random Variables

16. Binomial Distribution: Let p = probability of “success” q=probability of “failure” = 1-p n = number of trails r = number of “success” in “n” trails Then the probability of r successes for n trials is given by the following general formula: Probability Distributions, Discrete Random Variables

17. Probability Distributions, Continuous Variables Objectives: (Chapter 6, DeCoursey) - To establish the difference between probability distribution for discrete and continuous variables. - To learn how to calculate the probability that a random variable, X, will fall between the limits of “a” and “b”.

18. Continuous Variable Discrete Variable