Statistical inference; estimation, confidence intervals, hypothesis testing; analysis of variance; goodness of fit tests; regression and correlation analysis; Bayesian methods; introduction to design of experiments; use of statistical software.
Statistical Modelling (MATH 306)
2021 Spring
Faculty of Engineering and Natural Sciences
Mathematics(MATH)
3
6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Semih Onur Sezer sezer@sabanciuniv.edu,
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English
Undergraduate
MATH203
Formal lecture,Interactive lecture,Recitation
Interactive,Learner centered,Communicative,Discussion based learning
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Decision and Behavior |
CONTENT
OBJECTIVE
- To introduce the basic techniques of point and interval estimation
- To teach how to design and test hypotheses
- To teach the principles of regression analysis
LEARNING OUTCOME
Identify special sampling distributions
Apply the techniques of point estimation for parameters of interest and assess the quality of these estimators
Construct confidence intervals of parameters of interest
Apply the classical approach to hypothesis testing
Apply and implement special statistical tests
Fit and interpret linear regression models.
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ASSESSMENT METHODS and CRITERIA
Percentage (%) | |
Final | 50 |
Midterm | 50 |
RECOMENDED or REQUIRED READINGS
Textbook |
Probability and Statistics for Engineering and the Sciences by Devore, 9th Edition, Cengage 2016 John E. Freund's Mathematical Statistics with Applications, by I.Miller & M.Miller, 8th ed., Pearson International, 2014. |