1.1) What is Statistics

1.2) Sampling Procedures

1.3) Measures of Location

1.4) Measure of Variability

1.5) Discrete and Continuous Data

1.6) Graphical Diagnostics

2.1) Set, Sample Space and Events

2.2) Permutation and Combination

2.3) Probability of an Events

2.4) Rules of Probability

2.5) Conditional Probability

2.6) Independent Events

2.7) Bayes’ Theorem

3.1) Random Variables

3.2) Discrete Random Variable 

• Probability Distribution; 

• Distribution Function; 

• Mathematical Expectations

3.3) Continuous Random Variable 

• Probability Density Distribution; 

• Distribution Function; 

• Mathematical Expectations

3.4) Moment and Moment-Generating Function

4.1) Discrete Distributions 

• Uniform Distribution; 

• Bernoulli Distribution; 

• Binomial Distribution; 

• Geometric Distribution; 

• Poisson Distribution; 

• Poisson Approximation to Binomial

4.2) Continuous Distributions 

• Uniform Distribution; 

• Exponential Distribution; 

• Normal Distribution; 

• Normal Approximation to the Binomial; 

• Normal Approximation to the Poisson

5.1) Discrete Bivariate Probability Distributions

•  Marginal Distributions; 

• Conditional Distributions; 

• Mathematical Expectations

5.2) Continuous Bivariate Probability Distributions 

• Marginal Distributions;

• Conditional Distributions; 

• Mathematical Expectations