1. komponenta

Vrsta nastave	Ukupno
Predavanja	30
Auditorne vježbe	30

* Opterećenje je izraženo u školskim satima (1 školski sat = 45 minuta)

COURSE OBJECTIVES:
To train students for planning statistical experiments or observations, analysis of data and statistical inference about population based on sample by use of standard statistical models and methods for:

1. Comparison and testing laws of distribution,
2. Regression analysis,
3. Model selection,
4. Interval and point estimation of model parameters and hypothesis testing,
5. Valuation of model fit,
6. Dimension reduction,
7. Classification/discrimination of data,
8. Analysis of survival based on censored data.

COURSE CONTENT:
1. Nonparametric methods for law comparison. Rank tests (Mann-Whitney-Wilcoxon statistics, Spearman's coefficient of correlation), Kolmogorov-Smirnov tests, Tests of normality (Lilliefors test), ROC curve.
2. Multivariate data. Normal distribution, Multiple confidence intervals and multiple testing, Multiple correlation, Partial correlation, Linear regression models (Kronecker product, Gauss-Markov properties, model selection), MANOVA and MANCOVA models, Allocation and discrimination, Principal component analysis (the best linear prediction).
3. Log-linear models. Parameter estimation, Prediction, Wald test, Model selection.
4. Computer intensive methods. Monte Carlo methods, Bootstraping, Cross-validation, Permutation tests.
5. Survival analysis. Kaplan-Meier estimator, Cox proportional-hazards model.

1. Statistica Concepts and Methods, Bhattacharyya, G.K., Johnson, R.A., Wiley, 1977.
2. Theory of Multivariate Statistics, Bilodeau, M., Brenner, D., Springer-Verlag, 1999.
3. Advanced Linear Modeling, 2nd ed., Christensen, R., Springer, 2001.
4. Bootstrap Methods and their Application, Davison, A.C., Hinkley, D.V., Cambridge UC, 1997.
5. Survival Analysis, Techniques for Censored and Truncated Data, Klein, J.P., Moeschberger, M.L., Springer, 1997.
6. Logistic Regression, 3rd ed., Kleinbaum, D.G., Klein, M., Springer, 2010.
7. Fundamentals of Mathematical Statistics, Nguyen, H.T., Rogers, G.S., Springer Verlag, 1989.
8. Cross-Validatory Choice and Assessment of Statistical Predictions, Stone, M, J R Stat Soc Ser B Methodol 36, 1974.
9. Plane Answers to Complex Questions, The Theory of Linear Models, 4th ed., Christensen, R., Springer, 2011.
10. Introductory Statistics with R, 2nd ed., Dalgaard, P., Springer, 2008.
11. A Course in Large Sample Theory, Ferguson, T.S., Chapman & Hall/CRC, 1996.
12. Randomization, Bootstrap, and Monte Carlo Methods in Biology, 3rd ed., Manly, B.F.J., Chapman & Hall/CRC, 2007.
13. Permutation Methods, Mielke, P.W. Jr., Berry, K.J., Springer, 2001.
14. Numerical Methods in Statistics, Monahan, J.F., Cambridge UP, 2001.
15. Stat Labs, Mathematical Statistics Through Applications, Nolan, D., Speed, T., Springer, 2000.
16. All of Statistics, Wasserman, L., Springer, 2004.
17. Fundamentals of Modern Statistical Methods, Wilcox, R.R., Springer, 2001.

Upis predmeta :
Odslušan : Statistics 1

Polaganje predmeta :
Položen : Statistics 1

Obavezni predmet - Redovni Studij - Biomedicinska matematika