The purpose of this course is to help the student to easily understand the theory of statistics, to comprehend the utility of the application of statistical methods in the various sectors of engineer's occupation and to gain the ability to use all of these methods and techniques in order to solve real problems.
The aim of the course is the understanding of basic principles of probability theory and statistical analysis and their application to problems in industrial production and management. Upon successful completion of this course, the student will be able to: • Define mathematical models for systems characterized by uncertainty • Solve these models to evaluate the performance of the systems they describe • Analyze data using statistical techniques and use the results of the analysis to make decisions
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Probability: concept of probability, conditional probability, multiplicative law, stochastic independence, Bayes rule. Random variables: discrete and continuous random variables, probability mass function, probability density function, moments (mean, variance), variable transformation, joint probability mass function, covariance, correlation coefficient. Random variable distributions: uniform, binomial, geometric, Poisson, normal, exponential. Statistical estimates: sampling, point estimates, properties and distributions of estimates, central limit theorem, confidence intervals.
Level:
Type:
Undergraduate
(A-)
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