Some Continuous Probability Distributions By: Prof. Gevelyn B. Itao.

Slides:



Advertisements
Similar presentations
The Normal Distribution
Advertisements

Special random variables Chapter 5 Some discrete or continuous probability distributions.
JMB Chapter 6 Part 1 v4 EGR 252 Spring 2012 Slide 1 Continuous Probability Distributions Many continuous probability distributions, including: Uniform.
Exponential Distribution. = mean interval between consequent events = rate = mean number of counts in the unit interval > 0 X = distance between events.
JMB Chapter 6 Part 1 v2 EGR 252 Spring 2009 Slide 1 Continuous Probability Distributions Many continuous probability distributions, including: Uniform.
E(X 2 ) = Var (X) = E(X 2 ) – [E(X)] 2 E(X) = The Mean and Variance of a Continuous Random Variable In order to calculate the mean or expected value of.
Lecture (10) Mathematical Expectation. The expected value of a variable is the value of a descriptor when averaged over a large number theoretically infinite.
Statistical Review for Chapters 3 and 4 ISE 327 Fall 2008 Slide 1 Continuous Probability Distributions Many continuous probability distributions, including:
Probability theory 2010 Order statistics  Distribution of order variables (and extremes)  Joint distribution of order variables (and extremes)
Continuous Random Variables. For discrete random variables, we required that Y was limited to a finite (or countably infinite) set of values. Now, for.
Engineering Probability and Statistics - SE-205 -Chap 4 By S. O. Duffuaa.
Probability Distributions – Finite RV’s Random variables first introduced in Expected Value def. A finite random variable is a random variable that can.
Today Today: Chapter 5 Reading: –Chapter 5 (not 5.12) –Suggested problems: 5.1, 5.2, 5.3, 5.15, 5.25, 5.33, 5.38, 5.47, 5.53, 5.62.
1 Engineering Computation Part 6. 2 Probability density function.
Descriptive statistics Experiment  Data  Sample Statistics Experiment  Data  Sample Statistics Sample mean Sample mean Sample variance Sample variance.
Lesson #15 The Normal Distribution. For a truly continuous random variable, P(X = c) = 0 for any value, c. Thus, we define probabilities only on intervals.
CSE 221: Probabilistic Analysis of Computer Systems Topics covered: Continuous random variables Uniform and Normal distribution (Sec. 3.1, )
Stat 321 – Day 15 More famous continuous random variables “All models are wrong; some are useful” -- G.E.P. Box.
A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.
The moment generating function of random variable X is given by Moment generating function.
Some Continuous Probability Distributions Asmaa Yaseen.
4-1 Continuous Random Variables 4-2 Probability Distributions and Probability Density Functions Figure 4-1 Density function of a loading on a long,
CIS 2033 based on Dekking et al. A Modern Introduction to Probability and Statistics, 2007 Instructor Longin Jan Latecki Chapter 7: Expectation and variance.
Moment Generating Functions 1/33. Contents Review of Continuous Distribution Functions 2/33.
JMB Ch6 Lecture 3 revised 2 EGR 252 Fall 2011 Slide 1 Continuous Probability Distributions Many continuous probability distributions, including: Uniform.
Statistics for Engineer Week II and Week III: Random Variables and Probability Distribution.
Moment Generating Functions
Random Variables and Stochastic Processes –
QBM117 Business Statistics Probability and Probability Distributions Continuous Probability Distributions 1.
JMB Ch6 Lecture2 Review EGR 252 Spring 2011 Slide 1 Continuous Probability Distributions Many continuous probability distributions, including: Uniform.
Copyright © 2010 Pearson Addison-Wesley. All rights reserved. Chapter 6 Some Continuous Probability Distributions.
4-1 Continuous Random Variables 4-2 Probability Distributions and Probability Density Functions Figure 4-1 Density function of a loading on a long,
Chapter 12 Continuous Random Variables and their Probability Distributions.
§ 5.3 Normal Distributions: Finding Values. Probability and Normal Distributions If a random variable, x, is normally distributed, you can find the probability.
Statistics. A two-dimensional random variable with a uniform distribution.
Probability Refresher COMP5416 Advanced Network Technologies.
INTRODUCTORY MATHEMATICAL ANALYSIS For Business, Economics, and the Life and Social Sciences  2011 Pearson Education, Inc. Chapter 16 Continuous Random.
School of Information Technologies Poisson-1 The Poisson Process Poisson process, rate parameter e.g. packets/second Three equivalent viewpoints of the.
CONTINUOUS RANDOM VARIABLES
Probability and Statistics Dr. Saeid Moloudzadeh Uniform Random Variable/ Normal Random Variable 1 Contents Descriptive Statistics Axioms.
Mean and Variance for Continuous R.V.s. Expected Value, E(Y) For a continuous random variable Y, define the expected value of Y as Note this parallels.
1 1 Slide Continuous Probability Distributions n The Uniform Distribution  a b   n The Normal Distribution n The Exponential Distribution.
Chapter 4 Continuous Random Variables and Probability Distributions  Probability Density Functions.2 - Cumulative Distribution Functions and E Expected.
Statistics -Continuous probability distribution 2013/11/18.
Jacek Wallusch _________________________________ Statistics for International Business Lecture 8: Distributions and Densities.
4-1 Continuous Random Variables 4-2 Probability Distributions and Probability Density Functions Figure 4-1 Density function of a loading on a long,
Random Variable 2013.
Chapter 4 Continuous Random Variables and Probability Distributions
Continuous Probability Distributions Part 2
The Exponential and Gamma Distributions
CONTINUOUS RANDOM VARIABLES
Chapter 7: Sampling Distributions
Multinomial Distribution
Some Continuous Probability Distributions
Moment Generating Functions
Working with Continuous Random Variables and the Normal Distribution
Distributions and expected value
Continuous Probability Distributions Part 2
Chapter 6 Some Continuous Probability Distributions.
Continuous Probability Distributions Part 2
Continuous Probability Distributions Part 2
Continuous Probability Distributions Part 2
Chapter 3 : Random Variables
Continuous Probability Distributions
Chapter 7 The Normal Distribution and Its Applications
Random Variables A random variable is a rule that assigns exactly one value to each point in a sample space for an experiment. A random variable can be.
Continuous Probability Distributions Part 2
PROBABILITY AND STATISTICS
Uniform Probability Distribution
Moments of Random Variables
Presentation transcript:

Some Continuous Probability Distributions By: Prof. Gevelyn B. Itao

 The density function of the continuous uniform random variable X on the interval [A, B] is

and

 The continuous random variable X has a gamma distribution, with parameters α and β, if its density function is given by where α > 0 and β > 0.

The gamma function is defined by where α > 0.

and µ = αβσ 2 = αβ 2

 The continuous random variable X has an exponential distribution, with parameter β, if its density function is given by where β > 0.

and µ = βσ 2 = β 2