Contents |
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Course Code
IAM 530 (9700530)
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Credit
(3-0) 3
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Prerequisites
Consent of the instructor
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Content/ Aims
Part I. Probability spaces. Random variables. Probability distributions and probability densities. Conditional probability. Bayes Formula. Mathematical expectation. Moments.
Part II. Sampling distributions. Decision Theory. Estimation (theory and applications). Hypothesis testing (theory and applications). Regression and correlation. Analysis of variance. Non-parametric tests.
The objective of this course is to initiate students to Probability Calculus and statistical methods used in current application problems.
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Learning Outcomes
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Suggested Textbooks
- Mathematical Statistics, J.E. Freund, Pentice Hall, 1992
- Introduction to Probability and Statistics, J.S. Milton and J.C. Arnold, McGraw-Hill, 1995
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Outline
- Probability spaces. Conditional probability, Bayes Formula, (1 week)
- Random variables, distribution functions, independence of random variables, funtions of random variables, (2 weeks)
- Mathematical expectation and moments, Markov and Chebyshev inequalities, (1 week) *DecisionTheory, (1 week)
- Estimation Theory, (2 weeks)
- Hypothesis testing, (2 weeks)
- Regression and correlation, (2 weeks)
- Analysis of vaiance, (2 weeks)
- Non-parametric tests, (1 week)