Presentation is loading. Please wait.

Presentation is loading. Please wait.

Www.soran.edu.iq Probability and Statistics Dr. Saeid Moloudzadeh Uniform Random Variable/ Normal Random Variable 1 Contents Descriptive Statistics Axioms.

Published bySuzanna Norman Modified over 9 years ago

Similar presentations

Presentation on theme: "Www.soran.edu.iq Probability and Statistics Dr. Saeid Moloudzadeh Uniform Random Variable/ Normal Random Variable 1 Contents Descriptive Statistics Axioms."— Presentation transcript:

1 www.soran.edu.iq Probability and Statistics Dr. Saeid Moloudzadeh Uniform Random Variable/ Normal Random Variable 1 Contents Descriptive Statistics Axioms of Probability Combinatorial Methods Conditional Probability and Independence Distribution Functions and Discrete Random Variables Special Discrete Distributions Continuous Random Variables Special Continuous Distributions Bivariate Distributions

2 www.soran.edu.iq Probability and Statistics Contents Descriptive Statistics Axioms of Probability Combinatorial Methods Conditional Probability and Independence Distribution Functions and Discrete Random Variables Special Discrete Distributions Continuous Random Variables Special Continuous Distributions Bivariate Distributions 2

3 www.soran.edu.iq Chapter 7: Special Continuous Distributions Context Uniform Random Variable. Normal Random Variable. Exponential Random Variables. Gamma Distribution. Beta Distribution. 3

4 www.soran.edu.iq Chapter 7: Special Continuous Distributions Context Uniform Random Variable. Normal Random Variable. Exponential Random Variables. Gamma Distribution. Beta Distribution. 4

Download ppt "Www.soran.edu.iq Probability and Statistics Dr. Saeid Moloudzadeh Uniform Random Variable/ Normal Random Variable 1 Contents Descriptive Statistics Axioms."

Similar presentations

Probability Distribution

Probability Distribution
Special random variables Chapter 5 Some discrete or continuous probability distributions.

Special random variables Chapter 5 Some discrete or continuous probability distributions.
Some additional Topics. Distributions of functions of Random Variables Gamma distribution,  2 distribution, Exponential distribution.

Some additional Topics. Distributions of functions of Random Variables Gamma distribution,  2 distribution, Exponential distribution.
Functions of Random Variables Notes of STAT 6205 by Dr. Fan.

Functions of Random Variables Notes of STAT 6205 by Dr. Fan.
Www.soran.edu.iq Probability and Statistics Dr. Saeid Moloudzadeh Frequency table and graphs 1 Contents Descriptive Statistics Axioms of Probability Combinatorial.

Probability and Statistics Dr. Saeid Moloudzadeh Frequency table and graphs 1 Contents Descriptive Statistics Axioms of Probability Combinatorial.
Some Continuous Probability Distributions By: Prof. Gevelyn B. Itao.

Some Continuous Probability Distributions By: Prof. Gevelyn B. Itao.
Www.soran.edu.iq Probability and Statistics Dr. Saeid Moloudzadeh Sample Space and Events 1 Contents Descriptive Statistics Axioms of Probability Combinatorial.

Probability and Statistics Dr. Saeid Moloudzadeh Sample Space and Events 1 Contents Descriptive Statistics Axioms of Probability Combinatorial.
Review of Basic Probability and Statistics

Review of Basic Probability and Statistics
Probability and Statistics for Engineers (ENGC 6310) Review.

Probability and Statistics for Engineers (ENGC 6310) Review.
Probability theory 2010 Order statistics  Distribution of order variables (and extremes)  Joint distribution of order variables (and extremes)

Probability theory 2010 Order statistics  Distribution of order variables (and extremes)  Joint distribution of order variables (and extremes)
1 Engineering Computation Part 6. 2 Probability density function.

1 Engineering Computation Part 6. 2 Probability density function.
Statistics 270 - Lecture 16. Gamma Distribution Normal pdf is symmetric and bell-shaped Not all distributions have these properties Some pdf’s give a.

Statistics Lecture 16. Gamma Distribution Normal pdf is symmetric and bell-shaped Not all distributions have these properties Some pdf’s give a.
Programme in Statistics (Courses and Contents). Elementary Probability and Statistics (I) 3(2+1)Stat. 101 College of Science, Computer Science, Education.

Programme in Statistics (Courses and Contents). Elementary Probability and Statistics (I) 3(2+1)Stat. 101 College of Science, Computer Science, Education.
2003/02/13 Chapter 4 1頁1頁 Chapter 4 : Multiple Random Variables 4.1 Vector Random Variables.

2003/02/13 Chapter 4 1頁1頁 Chapter 4 : Multiple Random Variables 4.1 Vector Random Variables.
Descriptive statistics Experiment  Data  Sample Statistics Experiment  Data  Sample Statistics Sample mean Sample mean Sample variance Sample variance.

Descriptive statistics Experiment  Data  Sample Statistics Experiment  Data  Sample Statistics Sample mean Sample mean Sample variance Sample variance.
Samples vs. Distributions Distributions: Discrete Random Variable Distributions: Continuous Random Variable Another Situation: Sample of Data.

Samples vs. Distributions Distributions: Discrete Random Variable Distributions: Continuous Random Variable Another Situation: Sample of Data.
A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.

A random variable that has the following pmf is said to be a binomial random variable with parameters n, p The Binomial random variable.
2. Random variables  Introduction  Distribution of a random variable  Distribution function properties  Discrete random variables  Point mass  Discrete.

2. Random variables  Introduction  Distribution of a random variable  Distribution function properties  Discrete random variables  Point mass  Discrete.
Mutually Exclusive: P(not A) = 1- P(A) Complement Rule: P(A and B) = 0 P(A or B) = P(A) + P(B) - P(A and B) General Addition Rule: Conditional Probability:

Mutually Exclusive: P(not A) = 1- P(A) Complement Rule: P(A and B) = 0 P(A or B) = P(A) + P(B) - P(A and B) General Addition Rule: Conditional Probability:
5-1 Two Discrete Random Variables Example 5-1 5-1 Two Discrete Random Variables Figure 5-1 Joint probability distribution of X and Y in Example 5-1.

5-1 Two Discrete Random Variables Example Two Discrete Random Variables Figure 5-1 Joint probability distribution of X and Y in Example 5-1.

Similar presentations

Ads by Google