Applied Biostatistic: A multivariate approach
Carlos Alberto Cardozo Delgado
II-2020
1 Lecturer
- Ph.D Carlos Alberto Cardozo Delgado, Full Research Professor - Universidad Manuela Beltran
- email: carlos.cardozo@docentes.umb.edu.co
2 Program
- This is a course of the Master of Biostatistics
3 Some important facts
- It is assumed that you have some experience with statistical concepts, such as, independence, estimators, multiple linear regression model, hypothesis tests.
- In this course we will write programs in the language R. But, if you code in another language, for instance, Python or Matlab, it is also fine.
- Each session have a duration of two hours.
4 General Objective
To evaluate through several techniques the joint behaviour of a set of random multivariate vectors.
5 Topics
In this course we will cover the following topics:
5.1 Matrix Algebra
5.2 Cluster Analysis
5.3 PCA Analysis
5.4 Correspondence Analysis
5.5 Discriminant Analysis
5.6 Factor Analysis
5.7 Canonical Correlation Analysis
6 Grading
This course will be grade based on assignments and two exam. The weigths of each activity are:
- Assignments 30%
- 19/09 Midterm exam 35%
- 28/11 Final exam 35%
7 Bibliography
- Casella G. and Berger, G. (2000). Statistical Inference, Second Edition.
- Gareth, J., Witten, D., Hastie, T., and Tibshirani R. (2017). An introduction to Statistical Learning with applications in R, Springer.
- Johnson, R. and Wichern, D. (2009). Applied Multivariate Statistical Analysis. Sixth Edition, Pearson - Prentice Hall
- R Core Team, R: A language and environment for statistical computing, R Foundation for Statistical Computing, 2019.
- Rencher, A. and Cristensen, W.(2012). Methods of Multivariate Analysis. Third Edition, John Wiley and Son.
If you want to know more about this course, please let me know:
