Introducing some computational techniques and algorithms used by statistical researchers and practitionersintroducing some computational techniques and algorithms used by statistical researchers and practitioners
a. Monte Carlo Statistical Methods by Christian P. Robert & George Casella
b. The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, Jerome Friedman
c. Statistical Computing by William J. Kennedy & James E. Gentle
d. Elements of Statistical Computing by Ronald A. Thisted
e. Bayesian Statistical Modeling by Peter Congdon
f. An Introduction to the Bootstrap by Bradley Efron and Robert J. Tibshirani
g. Simulation by Sheldon M. Ross
h. Modern Applied Statistics with S-Plus by W. N. Venables and B. D. Ripley
a. Monte Carlo Statistical Methods by Christian P. Robert & George Casella
b. The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, Jerome Friedman
c. Statistical Computing by William J. Kennedy & James E. Gentle
d. Elements of Statistical Computing by Ronald A. Thisted
e. Bayesian Statistical Modeling by Peter Congdon
f. An Introduction to the Bootstrap by Bradley Efron and Robert J. Tibshirani
g. Simulation by Sheldon M. Ross
h. Modern Applied Statistics with S-Plus by W. N. Venables and B. D. Ripley
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| Homework assignmentsHomework assignments homework assignments |
30 | |
| Midterm and/or FinalMidterm and/or Final midterm stable/or final |
40 | |
| Projects/PresentationsProjects/Presentations projects/presentations |
30 |
