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OWINFO course info
Lecture notes
Data sets
Previous examinations
Teaching schedule
Download R
Start with R
Introduction to R
Install Statgraphics
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This course is the successor of the course 2S990.
Lecturer:
A. Di Bucchianico, HG 10.17, phone
+31 (0)40 247 2902, email:
Instructor: S. Kuhnt, HG 10.23, phone +31 (0)40 247 2208, email:
Prerequisites: in order to successfully participate in this course, it
is essential to have passed the examination for the course 2S270:
Probability theory and statistics.
Software: R, to be obtained from www.r-project.org, and Statgraphics (to be obtained from the TU/e software website)
. I wrote an introduction to R which includes some exercises.
There is a PowerPoint presentation for a very quick introduction to R .
Material:
- Lecture notes Measures of Location and Scale
- Bain and Engelhardt, Introduction to probability and mathematical
statistics, Brooks/Cole, 2000.
- Statistisch Compendium (lecture notes nr. 2218)
Previous examinations
- November 30, 2001 (written
examination + solutions in Dutch)
- January 25, 2002 (written
examination + solutions in Dutch)
- November 28, 2002 (written
examination + solutions in Dutch).
- January 24, 2003 (written
examination + solutions in Dutch).
- November 27, 2003 (written examination + solutions
in Dutch).
- January 23, 2004 (written examination)
- November 26, 2004 (written examination)
- January 21, 2005 (written examination)
- November 25, 2005 (written examination + solutions in Dutch)
- January 19, 2006 (written examination + solutions in Dutch)
- January 25, 2007 (written examination )
- March 23 , 2007 (written examination + solutions in Dutch)
- November 14, 2007 (written examination + solutions in Dutch)
Data sets
In lecture notes (LN): copper (Example 1.1), suicide ( Example 1.2) , darwin (Example 1.3) and mercury (Example 1.13)
In Section 1.3 of Introduction to R (IR): eggs, supermarket, telephone, light, and clouds.
In Bain and Engelhardt (BE): example 4.6.3 = example 11.1.1, exercise 4.24 = exercise 11.2
Schedule
| Week |
Topic |
Sections in lecture (LN). Introduction to R (IR), or book (BE) |
Recommended exercises (new 2007-2008 numbering!) |
| 1 |
Statistical
software, measures of location and dispersion, boxplots
|
LN 1.1-1.3,
IR 1.1-1.2 ,
R script |
LN 1.12, IR 5, 6, 7, LN 1.9, 1.14;
solutions: IR 5, 6, 7 |
| 2 |
Empirical distributions and equivariance |
LN 1.4-1.5
R script |
IR 8; LN 1.15, 1.17, 1.18, 1.6
solution: IR 8 |
| 3 |
Outliers; Point estimation: construction (MME and ML) |
LN 1.6.1-1.6.2;
BE 9.1-9.2
R script
|
LN 1.22, 1.26, 1.28 ; BE 9.1, 9.4, 9.5, 9.8: examination Nov. 2005: 4a, Jan. 2006: 4b |
| 4 |
Point estimation: M-estimators, performance |
LN 1.7.1-1.7.2, BE 8.1, 8.2, 9.3, 9.4 only pp. 316-318 |
BE 9.17, 9.22, 9.24, 9.33, 9.34 a-f, 9.40, LN 1.41, 1.45, 1.46, examination Nov. 2003: 3, Nov. 2005: 4c, Jan. 2006: 2 |
| 5 |
no teaching |
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|
| 6 |
Sufficiency and completeness |
BE 10.1 - 10.3, 10.4 only definition of completeness +
Lehmann-Scheffé |
BE 10.1, 10.2, 10.10, 10.21,
10.31, examination Nov. 2002: 1 a-b, Nov. 2003: 1, Jan. 2004: 2, Nov. 2005: 4b, Jan. 2006: 4a |
| 7 |
Sampling distributions |
BE 8.3 - 8.5 |
(use both statistical tables and R): IR 1, 2, 3; BE 8.1, 8.5, 8.8, 8.10, 8.11, 8.16,
8.17 a+b; examination Nov. 2002: 3b, Jan. 2006: 3a + 4c |
| 8 |
Interval estimation
(small R script to compute confidence intervals) |
BE 11.1 - 11.3,11.5 |
(use both statistical tables and R): BE 11.1, 11.2, 11.4, 11.12, 11.20, 11.29 a-b, IR: 9, examination Nov. 2003: 5, Jan. 2004: 4c, Nov. 2005: 4b, Jan. 2006: 1c, 3b |
| 9 |
Hypothesis testing |
BE 12.1 - 12.5;
|
BE 12.1, 12.3, 12.5, 12.8, 12.9, IR: 11, 12, examination Nov. 2001: 2 a+b, Nov.
2002: 5, Jan. 2003: 5, Nov. 2005: 1 , Jan. 2006: 1 |
| 10 |
Hypothesis testing |
BE 12.6 - 12.8 |
BE 12.16, 12.17, 12.27, examination Jan. 2003: 4 , Nov. 2005: 5 , Jan. 2006: 5 |
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