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Course No. & Code:
Descriptive statistics: Statistical data classification; measures of central tendency (mean, mode, median); measures
of dispersion (variance, standard deviation, coefficient of variation). The theory of probabilities with applications to
science and engineering: introduction; properties; applications. The random variables: Discrete and continuous
random variables; expected value and variance of random variables; sums of discrete random variables; law of large
numbers. Discrete & continuous distributions or engineering applications; Joint, marginal, conditional distributions.
Selected distributions: Binomial, Poisson, Exponential, Weibull, Normal and Lognormal distributions. Basic
concepts and methods of statistics: sampling, sampling distributions, parameters estimation, hypotheses testing.
Analysis of variance; Correlation, simple and multiple linear regressions. Statistical software & its application.