STATISTICS


GENERAL DESCRIPTION OF THE COURSE

During this course the student will acquire fundamental theoretical knowledge of basic mathematical statistics, combinatorics, probability, conditional probability, probability distributions (Binomial, Poisson and normal distribution) and confidence intervals.

 

COURSE CONTENTS

The course will cover the following topics:

  • data processing and sampling (average, variance and standard deviation, random variables, discrete and continuous variables)
  • events and exsperiments (elementary and composed events, operations of events)
  • probability and conditional probability (Bayes’ theorem)
  • combinatorics (permutations and combinations)
  • probability distributions (discrete and continuous distributions, mean value and variance, Binomial, Poisson and normal distribution, standardization of normal distribution, table of standard normal distribution)
  • confidence intervals (confidence interval of mean value of normal distribution at known/unknown variance, t-distribution, confidence interval of variance, chi-square distribution)
  • testing of hypotheses

 

STUDY MATERIALS:

E. Kreyszig: Advanced Engineering Mathematics, 10th edition, John Willey and Sons, New York