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Statistics e-texts
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.
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