Probability and Statistics

Course Aim:
This course introduces the basic concepts of probability and statistics and their applications.
Course contents:
Statistical experiments, sample space, events, operations on events, Combinatorial analysis: Permutations, Combinations and Counting rules, Definition of the probability and probability axioms, Conditional probability, Independence of events and Bayes theorem, Definition of the random variable, Some special discrete probability distributions: binomial distribution, Poisson distribution, geometric distribution, hypergeometric distribution, Some special continuous probability distributions, Introduction and overview of statistics, Data description using measures of central tendency, Measures of dispersion,  Measures of position, Sampling distribution, Central limit theorem, Interval estimation, confidence interval, Hypothesis testing, Computing Application.