Introduction to Statistics. Random Variable, Mean, Variance, Standard Deviation and Mathematical Expectation. ...
(more)
Introduction to Statistics. Random Variable, Mean, Variance, Standard Deviation and Mathematical Expectation. Discrete Distributions: Bernoulli trials and Bernoulli distribution, geometric distribution, Poisson distribution. Continuous Distributions: random variables of the continuous type, uniform distribution, exponential distribution, gamma distribution, chisquare distribution, normal distribution, tdistributions. Estimation: biased and unbiased esimators, convidence intervals for means, convidence intervals for variances, sample size, maximum error of the point estimate, Likelihood function, Maximum Likelihood Estimation (MLE), Asymptotic Distributions of Maximum Likelihood Estimators, Chebyshev's Inequality. Hypothesis: tests of statistical hypotheses, Type I error, Type II error, tests about proportions, null hypothesis, alternative hypothesis, significance level of the test, probability value, tailend probability, standard error of the mean, tests about one mean and one variance, test of the equality of two independent normal distributions, best critical region, NeymanPearson Lemma, most powerful test, uniformly most powerful critical region, Likelihood Ratio tests, critical region for the likelihood ratio test. PseudoNumbers: uniform pseudorandom variable generation, congruential generators, shiftregister generators, Fibonacci generators, Combinations of Generators (Shuffling). The Inverse Probability Method for Generating Random Variables. The Logistic Distribution.
(less)
 Subject:
 Mathematics and Statistics
 Material Type:
 Full Course
 Readings
 Syllabi
 Collection:

Connexions
 Provider:

Rice University
 Author:
 Ewa Wosik
No Strings Attached