An overview of modules |
Structure of Statistics e-texts |

0-1-Probability |
Introduction, Definition of probability, rules of probability and permutations and combinations |

1-1-Probability |
Conditional probability; Law of Total Probability; Bayes' Theorem; Statistical Independence. |

2-1-Discrete Random Variables |
Probability Function & Cumulative Distribution Function; Mean and Variance |

3-1-Special Discrete Dist's |
Uniform discrete; Binomial; Poisson; Poisson approximation to Binomial |

3-2-Continuous Distributions |
Continuous probability density function, cumulative distribution function, mean and variance. |

4-1-Special Continuous Dist's |
Uniform Distribution; Exponential Distribution; Normal Distribution; Normal approximation to Binomial & Poisson Distributions |

4-2-Joint Discrete Dist's |
Introduction; Finding averages and Statistical independence; Covariance and correlation |

5-1-Sampling Theorem |
Introduction; Statistics & sampling dist's; Sampling from a distribution; Sample max & min; Dist of sample mean from Normal dist; Dist of sample mean for large sample sizes |

6-1-Estimation |
Introduction & unbiased estimators; biased estimators & mean square error; Method of moments & maximum likelihood estimation. |

7-1-Confidence Intervals |
Confidence Intervals for means, difference of means, variance and ratio of variances |

8-1-Hypothesis Testing |
Introduction; Normal means with known and unknown variances; Difference of Normal means with known and unknown variances; Power functions. |

9-1-Regression & Correlation |
Least Squares Regression and Correlation, Confidence Intervals and Hypothesis Testing for parameters. |