Contents

1.Theory of Probability   

1.Counting Techniques

2.Deterministic and Non Deterministic Model    

3.Sample Spaces

4.Events  

5.Probability  

6.Theorems of Probability 

2.Conditional Probability and Independence

1. Conditional Probability

2. Bayes’ Theorem   

3. Definition of Sensitivity of a Procedure, Specificity of Procedure

4. Independence of Two Events

3. Random Variable

1. Introduction

2. Random Variable and Discrete and Continuous Random Variable 

3. Probability of Mass Function of Discrete Random Variable and Probability Density Function of Continuous

4. Distribution Function or Cumulative Distribution Function   

5. Expectation and Variance    

6. Determination of Median and Mode using p.m.f.    

4. Standard Discrete Distributions  

1. Introduction

2. Discrete Uniform Distribution    

3. Bernoulli Distribution 

4. Binomial Distribution  

5. Geometric Distribution 

6. Poisson Distribution