TI2216M

STAT 305

Course Info

International Credits: 5.0
Converted Credits: 3.0
Semester: fall
Country: Netherlands
Language: English
Course Description:
Axiomatic introduction of probability (space). Some elementary combinatorics to find probabilities. Conditional probability; Bayes' rule; stochastic (in)dependance. Random variable, probability mass functon, density function, distribution function. Standard distributions: Binomial, Poisson, Geometric, Normal, Uniform, Exponential. Expectation and variance; Jensen's inequality. Multivariate random variables; joint distribution; (in)dependance. (Conditional) Expectation, Covariance, Correlation. Cebychev's inequality; Law of Large numbers; Central Limit Theorem. Poisson process. Sampling theory; mean, sample variance, histogram, empirical distribution function, boxplot. Linear Regression. Theory of Estimators: Bias, Efficiency; Moment Estimators, Maximum Likelihood Estimators. Confidence intervals of Mean and Proportion. t-distribution Testing theory: Type I/II Error, p-value, significance level, critical region

Evaluation Date:
August 8, 2016
Evaluated:
Peter Sherman