MATH 2260 • Final • Probability and Statistics for Engineering

Probability Density Function (PDF) for Continuous RV

PDF Example

Cumulative Distribution Function (CDF) for Continuous RV

CDF Example

Continuous Uniform Distribution

Example 1

Example 2

Exponential Distribution

Example 3

Example 4

Memoryless Property

Example 5

Normal Distribution

Standard Normal Distribution

Reading Z Table - Option 1

Reading Z Table - Option 2

Example 6

Continuous Joint Random Variables

Marginal PDF and CDF for Continuous Joint RV

Conditional PDF and CDF for Continuous Joint RV

Expected Value for Discrete RV

Example 1

Example 2

Variance for Discrete RV

Example 3

Example 4

Expected Value for Continuous RV

Example 5

Example 6

Variance for Continuous RV

Example 7

Expected Value for Discrete Joint RV

Variance for Discrete Joint RV

Example 8

Expected Value and Variance for Continuous Joint RV

Covariance

Example 1

Example 2

Example 3

Variance of Sums

Example 4

Continuous Random Variable 1

Continuous Random Variable 2

Continuous Random Variable 3

Continuous Random Variable 4

Continuous Random Variable 5

Continuous Random Variable 6

Continuous Random Variable 7

Uniform Distribution 1

Uniform Distribution 2

Uniform Distribution 3

Exponential Distribution 1

Exponential Distribution 2

Exponential Distribution 3

Exponential Distribution 4

Normal Distribution 1

Normal Distribution 2

Normal Distribution 3

Normal Distribution 4

Normal Distribution 5

Normal Distribution 6

Normal Distribution 7

Discrete Random Variable 1- Expected Value

Discrete Random Variable 2 - Expected Value

Discrete Random Variable 3 - Variance

Discrete Random Variable 4- Expected Value

Discrete Random Variable 5 - Expected Value

Discrete Random Variable 6 - Expected Value and Variance

Continuous Random Variable 1 - Expected Value

Continuous Random Variable 2 - Expected Value

Continuous Random Variable 3 - Variance

Continuous Random Variable 4 - Expected Value

Continuous Random Variable 5 - Expected Value and Variance

Continuous Joint Distribution 1

Continuous Joint Distribution 2

Continuous Joint Distribution 3

Continuous Joint Distribution 4

Continuous Joint Distribution 5

Covariance 1

Covariance 2

Covariance 3

Covariance 4

Sample Mean

Sample Variance

Example 1

Central Limit Theorem

Example 2

Example 3

Example 4

Example 5

Example 6

Normal Approximation to Binomial Distribution

Normal Approximation to Poisson Distribution

Introduction

Table Values ( SADECE Z ve T KISIMLARI DAHİL)

Confidence Interval for Means( Sigma known)

Example 1

Example 2

Example 3

Exam-like Question 1

Confidence Interval for Means (sigma unknown)

Example 1

Example 2

Testing Procedure

How to Perform the Test for Means

Example 1

Example 2

Example 3

Example 4

Exam like Question 1

Exam like Question 2

Central Limit Theorem 1

Central Limit Theorem 2

Central Limit Theorem 3

Central Limit Theorem 4

Central Limit Theorem 5

Central Limit Theorem 6

Central Limit Theorem 7

Normal Approximation to Binomial 1

Normal Approximation to Binomial 2

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

Testing for the Mean 1

Testing for the Mean 2

Testing for the Mean 3

Testing for the Mean 4

Testing for the Mean 5

Testing for the Mean 6

Testing for the Mean 7

Testing for the Mean 8

Testing for the Mean 9