Course Code: EST 206
Course Title: Applied Statistical Analyses
Weekly Class and Application Hours: 3-2
Short Course Description: This course is based on statistical introductory concepts. It includes descriptive statistics on data sequences and series, convergence of sequences of real numbers, comparison, root and ratio tests for convergence of series of real numbers. Standard Distributions: Binomial, negative binomial, geometric, Poisson, hyper geometric, uniform, exponential, gamma, beta and normal distributions. Poisson and normal approximations of a binomial distribution. Testing of Hypotheses: Basic concepts, applications of Neyman – Pearson Lemma for testing simple and composite hypotheses. Q- and t- tests. Likelihood ratio tests for parameters of univariate normal distribution. Applications for the above concepts will be introduced in lab classes with the software package SPSS. Also, basic principles of the software MATLAB are introduced with data manipulation in matrices.
Textbook and Supplementary Books::
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Introduction to Linear Regression Analysis, 4th Edition, Montgomery, D. C., Peck E. A., and G. G. Vining, Wiley (2006) [required]
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Multivariate Statistical Methods: A Primer, 3rd Edition, Manly, D. F. J, Chapman and Hall (2004) Great reference for reviewing some elements of linear algebra, and for linear discriminant analysis, principal components analysis and canonical correlation analysis Efron, B. and R. J. Tibshirani,
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An Introduction to the Bootstrap, Chapman and Hall (1993)Johnson, R. A., and D. W. Wichern,
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Applied Multivariate Statistical Analysis, 5th Edition, Prentice Hall (2002) Venables, W. N., and B. D. Ripley,
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Modern Applied Statistics with S, 4th Edition, Springer (2002)
Course Assessment:
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Class Participation 10%,
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Mid-term Examination 30%,
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Assignments 10%,
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Final Examination 50%,
Attendance 95%compulsory