Multivariate Statistical Analysis
Credit Hours : 2
Students completing this course should understand basic concepts and application of multivariate analysis (Correlation and regression). They are expected to be able to conduct appropriate statistical methods and interpret the results for applications. Examples of programming will be demonstrated for data analyses during lectures.
1- A review on basic of statistics and its application in research
2- Simple linear regression and correlation
3- Matrix algebra and random vectors
4- Multivariate linear regression models
5- Non-linear regression
6-General Linear Models (GLM)
1-Draper, N. R., and H. Smith. 1981. Applied Regression Analysis. John Wiley and Sons. New York, USA
2-Montgomery, D. C. and E. A. Peck. 2007. Introduction to linear Regression Analysis. 5th edition. John Wiley and Sons. Newyork, USA.
3-Johnson, R. A. and D. W. Wichern. 2007. Applied multivariate statistical analysis. Prentice Hall Inter. Inc. New Jersey, USA.
Final Exam/Projects (50%)
Tud 08:00 - 10:00