MATH 230 • Tüm Sınavlar • Probability and Statistics for Engineering

Basic Principles of Counting

Counting Examples

Permutations

Permutations Example

Groups and Circular Permutation Example

Identical Objects Example 1

Identical Objects Example 2

Identical Objects Example 3

Combination

n choose r

Committee Example 1

Committee Example 2

Ball Example 1

Ball Example 2

Sample Space and Events

Probability

Axioms of Probability

Some Rules

Coin Example

Dice Example

Card Example 1

Card Example 2

Ball Example

Set Example

Birthday Example

Conditioning Events

Total Probability Rule

Example 1

Example 2

Example 3

Example 4

Example 5

Example 6

Independence

Independence Example 1

Independence Example 2

Counting 1

Counting 2

Counting 3

Counting 4

Axioms of Probability 1

Axioms of Probability 2

Axioms of Probability 3

Axioms of Probability 4

Conditional Probability 1

Conditional Probability 2

Conditional Probability 3

Conditional Probability 4

Independence 1

Independence 2

Conditional Probability and Independence

Random Variables

Probability Mass Function

PMF Example 1

PMF Example 2

Cumulative Distribution Function

CDF Example 1

Expected Value

Expected Value Example 1

Expected Value Example 2

Variance

Variance Example 1

Variance Example 2

Bernoulli Distribution - 1

Bernoulli Distribution - 2

Example 1

Binomial Distribution - 1

Binomial Distribution - 2

Example 2

Example 3

Negative Binomial Distribution - 1

Negative Binomial Distribution - 2

Example 4

Hypergeometric Distribution

Example 5

Poisson Distribution - 1

Poisson Distribution - 2

Example 6

Example 7

Poisson Approximation to Binomial Distribution

Example 8

Geometric Distribution Part 1

Geometric Distribution Part 2

Example 1

Example 2

Discrete Random Variables 1

Discrete Random Variables 2

Discrete Random Variables 3

Discrete Random Variables 4

Discrete Random Variables 5

Discrete Random Variables 6

Discrete Random Variable 7

Discrete Random Variables 8

Discrete Random Variable 9

Binomial Distribution 1

Binomial Distribution 2

Binomial Distribution 3

Binomial Distribution 4

Poisson distribution 1

Poisson Distribution 2

Poisson Distribution 3

Poisson distribution 4

Hypergeometric Distribution 1

Hypergeometric Distribution 2

Hypergeometric Distribution 3

Negative Binomial Distribution 1

Negative Binomial - Geometric Distribution

Geometric Distribution 1

Geometric Distribution 2

Geometric Distribution 3

Probability Density Function - PDF

Example 1

Cumulative Distribution Function - CDF

Example 2

Expected Value

Expected Value - Example 1

Expected Value - Example 2

Variance

Variance - Example 1

Uniform Distribution

Example 1

Example 2

Exponential Distribution

Example 3

Example 4

Memoryless Property

Example 5

Normal Distribution (Gaussian Distribution)

Standard Normal Distribution

Reading Z Table - Option 1

Reading Z Table - Option 2

Example 6

Gamma Distribution

Example 8

Relation of Gamma Distribution with Others

Introduction

Formulas

Properties

Example 1

Example 2

Example 3

Example 4

Example 5

Continuous Random Variables 1

Continuous Random Variables 2

Continuous Random Variables 3

Continuous Random Variables 4

Continuous Random Variables 5

Continuous Random Variables 6

Uniform Distribution 1

Uniform Distribution 2

Exponential Distribution 1

Exponential Distribution 2

Exponential Distribution 3

Exponential Distribution 4

Exponential Distribution 5

Normal Distribution 1

Normal Distribution 2

Normal Distribution 3

Normal Distribution 4

Normal Distribution 5

Normal Distribution 6

Normal Distribution 7

Moment Generating Function 1

Moment Generating Function 2

Moment Generating Function 3

Moment Generating Function 4

Moment Generating Function 5

Expected Value - Discrete Random Variable

Binomial and Geometric Distributions

Continuous Random Variable

Poisson Distribution

Probability Mass Function

PMF Example

Marginal PMF and CDF

Expected Value

Variance

Expected Value and Variance Example

Conditional PMF and CDF

Conditional Expectation

Example

End of Topic Questions 1

End of Topic Question 2

Introduction

Marginal PDF and CDF

Expected Value and Variance

Conditional PDF and CDF

Conditional Expectation

Example 1

Example 2

End of Topic Questions 1

End of Topic Question 2

Sample Mean

Sample Variance

Example 1

Central Limit Theorem

Example 2

Example 3

Jointly Distributed Discrete Random Variables 1

Jointly Distributed Discrete Random Variables 2

Jointly Distributed Discrete Random Variables 3

Jointly Distributed Continuous Random Variables 1

Jointly Distributed Continuous Random Variables 2

Jointly Distributed Continuous Random Variables 3

Jointly Distributed Continuous Random Variables 4

Central Limit Theorem 1

Central Limit Theorem 2

Central Limit Theorem 3

Introduction

Unbiased Estimators

Example 1

Example 2

Example 3

Example 4

Example 5

Efficient Estimator

Method of Moments

Example 1

Example 2

Example 3

Example 4

Method of Maximum Likelihood

Example 5

Example 6

Example 7

Example 8

Chapter Summary

Point Estimation 1

Point Estimation 2

Point Estimation 3

Point Estimation 4

Maximum Likelihood Estimation 1

Maximum Likelihood Estimation 2

Maximum Likelihood Estimation 3

Maximum Likelihood Estimation 4

Maximum Likelihood Estimators 5

Method of Moments and Maximum Likelihood

Method of Moments and Maximum Likelihood

Motivation

Reading Z Table

Confidence Interval for Means Using Z Distribution

Example 1

Example 2

Example 3

Reading T Table

Confidence Interval for Means Using T Distribution

Example 4

Example 5

Formula

Example 1

Example 2

Example 3

Exam like Question 1

C.I. of Mean (Known Variance) 1

C.I. of Mean (Known Variance) 2

C.I. of Mean (Known Variance) 3

C.I. of Mean (Unknown Variance) 1

C.I. of Mean (Unknown Variance) 2

C.I. of Mean (Unknown Variance) 3

C.I. of Variance 1

C.I. of Variance 2

C.I. of Variance 3

Question 1

Question 2

Question 3

Question 4

Question 5

Question 6

Question 7

Question 8

Question 9

Question 10

Question 11

Question 12

Question 13

Question 14

Question 15

Question 16

Question 17

Question 18

Question 19

Question 20

Question 21

Probability

Continuous Joint Probability

Functions of Random Variables

Point Estimation