ENMA 420-520 Lecture 3 Slides

# ENMA 420-520 Lecture 3 Slides - Statistical Concepts for...

This preview shows pages 1–9. Sign up to view the full content.

Click to edit Master subtitle style 10/17/09 Statistical Concepts for Engineering Management ENMA 420 / 520 Lecture #3 Discrete Random Variables 11

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
10/17/09 Basic Definitions Random Variable: A numerical-valued function defined over a sample space. Each simple event in the sample space is assigned a value of Y. Discrete Random Variable: One that can only assume a countable number of values. Binary state: {0, 1} 22
10/17/09 Probability Distribution A table, graph or formula that gives the probability p(y) associated with each possible value of Y = y. Example: For Y = {H, T}, may have p(H) = 0.5, p(T) = 0.5 Requirements: 0 <= p(y) < = 1 33

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
10/17/09 Exercise 4.4 a. The list of all possible pairs of beach hotspots is shown at right: b. The probabilities of each of these outcomes should all be equal if a random sampling Beach Hotspot Pair MBF CINY MBF SCA MBF MBNJ MBF OCNJ MBF SLNJ CINY SCA CINY MBNJ CINY OCNJ CINY SLNJ SCA MBNJ SCA OCNJ SCA SLNJ MBNJ OCNJ MBNJ SLNJ OCNJ SLNJ
10/17/09 Exercise 4.4 (Cont’d) c. The value of Y is found by determining the total number of beach hotspots in the sample with a planar nearshore bar condition. Beach Hotspot Pair P(Sample ) Y MBF CINY 1/15 0 MBF SCA 1/15 0 MBF MBNJ 1/15 1 MBF OCNJ 1/15 0 MBF SLNJ 1/15 1 CINY SCA 1/15 0 CINY MBNJ 1/15 1 CINY OCNJ 1/15 0 CINY SLNJ 1/15 1 SCA MBNJ 1/15 1 SCA OCNJ 1/15 0 SCA SLNJ 1/15 1 MBNJ OCNJ 1/15 1 MBNJ SLNJ 1/15 2 OCNJ SLNJ 1/15 1

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
10/17/09 Exercise 4.4 (Cont’d) d. The probability distribution for Y is found by grouping similar values of Y together in the table. Y = y P(Y) 0 6/15 1 8/15 2 1/15 e. P(Y ≥ 1) = P(1) + P(2) = 8/15 + 66 0 2 4 6 8 10 12 P(Y)
10/17/09 Exercise 4-8 77 0 2 4 6 8 10 12

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
10/17/09 5 Minute Break Assignment: Discuss examples of discrete random variables Discuss some random variables that would not be discrete 88
This is the end of the preview. Sign up to access the rest of the document.

## This note was uploaded on 10/17/2009 for the course MET 387 taught by Professor Dean during the Spring '09 term at Old Dominion.

### Page1 / 49

ENMA 420-520 Lecture 3 Slides - Statistical Concepts for...

This preview shows document pages 1 - 9. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online