'Discrete random variable' diaporamas de présentation

Mathematical Expectation Spiegel et al (2000) - Chapter 3

Mathematical Expectation Spiegel et al (2000) - Chapter 3. Examples by Mansoor Al-Harthy Maria Sanchez Sara Russell DP Kar Alex Lombardia Presented by Professor Carol Dahl. Introduction. Green Power Co. investment

1.5k views • 128 slides

Chapter 5:

Chapter 5:. DISCRETE RANDOM VARIABLES AND THEIR PROBABILITY DISTRIBUTIONS. RANDOM VARIABLES. Discrete Random Variable Continuous Random Variable. RANDOM VARIABLES cont. Table 5.1 Frequency and Relative Frequency Distribution of the Number of Vehicles Owned by Families. .

1.58k views • 114 slides

6.2 Probability Theory Longin Jan Latecki Temple University

6.2 Probability Theory Longin Jan Latecki Temple University. Slides for a Course Based on the Text Discrete Mathematics & Its Applications (6 th Edition) Kenneth H. Rosen based on slides by Michael P. Frank and Andrew W. Moore. Terminology.

1.2k views • 95 slides

Random Variables

Random Variables. an important concept in probability. A random variable , X, is a numerical quantity whose value is determined be a random experiment. Examples Two dice are rolled and X is the sum of the two upward faces.

1.96k views • 61 slides

723 views • 60 slides

Discrete Probability Distributions (Random Variables and Discrete Probability Distributions)

Discrete Probability Distributions (Random Variables and Discrete Probability Distributions). Chapter 5 BA 201. Random Variables. Random Variables. A random variable is a numerical description of the outcome of an experiment. A discrete random variable may assume either a

716 views • 52 slides

Random Variables and Probability Distributions

Random Variables and Probability Distributions. Modified from a presentation by Carlos J. Rosas-Anderson. Fundamentals of Probability. The probability P that an outcome occurs is: The sample space is the set of all possible outcomes of an event Example: Visit = {( Capture ), ( Escape )}.

795 views • 47 slides

Bruce Mayer, PE Licensed Electrical & Mechanical Engineer BMayer@ChabotCollege.edu

490 views • 42 slides

Expected Value Reprise

Expected Value Reprise. CP Canoe Club Duck Derby Maximum of 2 000 tickets sold $5/ticket Prizes 1) 12 VIP tickets to Cirque du Soleil ($2,000) 2) 32gb BlackBerry Playbook ($600) 3) $250 Should Mr. Lieff buy a ticket?. Expected Value Calculation. For 2 000 tickets

496 views • 34 slides

Chapter 1 Probability Theory ( i ) : One Random Variable

Bioinformatics Tea Seminar: Statistical Methods in Bioinformatics. Chapter 1 Probability Theory ( i ) : One Random Variable. 06/05/2008 Jae Hyun Kim. Content. Discrete Random Variable Discrete Probability Distributions Probability Generating Functions Continuous Random Variable

988 views • 26 slides

Discrete Probability Distributions

659 views • 20 slides

5-1 Random Variables and Probability Distributions

314 views • 19 slides

Biostatistics

424 views • 18 slides

Probability Distributions and Expected Value

Probability Distributions and Expected Value. In previous chapters, our emphasis was on the probability of individual outcomes. This chapter develops models for distributions that show the probabilities for all possible outcomes of an experiment. Random Variable (X).

291 views • 18 slides

STATISTICS FOR BUSINESS

STATISTICS FOR BUSINESS. Chapter 4 : Discrete data and probability. The shopping mall. STATISTICS FOR BUSINESS ( Discrete data and probability). The shopping mall. Discrete data is composed of integer values , or whole numbers

286 views • 11 slides

Chapter 7 Day 1

216 views • 11 slides

Chapter 7 Random Variables a variable whose value is a numerical outcome of a random phenomenon.

Chapter 7 Random Variables a variable whose value is a numerical outcome of a random phenomenon. 7.1 Discrete and Continuous Random Variables 7.2 Means and Variances of Random Variables. Turn in AP Registration. 7.1 Discrete and Continuous Random Variables. Discrete Random Variable

458 views • 11 slides

2 Discrete Random Variable

2 Discrete Random Variable. Independence (module 1). A and B are independent iff the knowledge that B has occurred does not change the probability that A occurs. A, B independent ? P[A|B] = P[A] A, B independent ? P(A ? B) = P(A) P(B). Random Variable (RV).

175 views • 10 slides

Learn Discrete Probability Distribution with CK-12 FlexBook

CK-12 FlexBooks explain that Data can be classified into two groups: discrete and continuous. To Learn basis of Random variables and Discrete Probability Distribution visit

353 views • 2 slides

Chapter 7

148 views • 0 slides