Statistics of Experimental Design

1. Ludolf E. Meester, Statistics Dept. Peter J.T. Verheijen, Chemical Eng. Dept. Statistics of Experimental Design wi2144st wi2144st

2. wi2144st

3. Aim • Introduction probability and statistics • Familiarise engineering students with the jargon of the statisticians • Model-based analysis of experimental data • Design of experiments wi2144st

4. Contents Probability Example 1: Probability of success in test Distributions Descriptive Statistics Estimation theory Example 2: Probability of success in test 2 given that test 1<5.5? Hypothesis testing Linear Model Non-linear regression Answer: 0.55 and 0.15 Design of experiment Model selection/discrimination wi2144st

5. Contents Probability Distributions Descriptive Statistics Estimation theory Hypothesis testing Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

6. Contents Probability Distributions Descriptive Statistics Estimation theory Hypothesis testing Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

7. Contents Descriptive Statistics Probability Distributions Example: What is mu and sigma? Estimation theory Estimation theory • Bias • Robustness • Confidence Interval • Bootstrap methods Hypothesis testing Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

8. Contents Descriptive Statistics Probability Example 1: When you have less than 4. 5 on test 1, you will not pass Distributions Estimation theory Hypothesis testing Example 2: Average Test1=Average Test 2 Linear Model Non-linear regression Answer: No and no Design of experiment Model selection/discrimination wi2144st

9. Contents Descriptive Statistics Probability Distributions Estimation theory Hypothesis testing Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

10. Contents Descriptive Statistics Probability Distributions Estimation theory Hypothesis testing Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

11. Contents Descriptive Statistics Probability Distributions Estimation theory … To improve estimate ... To improve prediction of model Hypothesis testing Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

12. Contents Descriptive Statistics Probability Given Data: Choose between models Distributions Estimation theory Hypothesis testing Given Different Models: Choose between experiments Linear Model Non-linear regression Design of experiment Model selection/discrimination wi2144st

13. The Lectures • Introduction, probability • Probability distributions • Simulation, expectation and variance • Joint distributions • Central limit theorem, data exploration • Estimation • Hypothesis testing • Stochastic vectors: linear model and estimation • Linear model, confidence interval and hypothesis testing • Linear model, Non-linear regression • Non-linear regression • Experimental design • Model selection • Review wi2144st

14. Overview Entities Data = Model + Experimental Error Actions Characterisation Experimentation Estimation Hypothesis testing … to be continued wi2144st

15. Course Material and Information • Part I: A Modern Introduction to Probability and • Statistics by Dekking et al, ISBN 1-85233-896-2; • (Autumn 2004 and later versions of Kanstat lecture notes still usable.) • Part II: Lecture Notes, plus exercises • Exercises and Examination Set Edition 7 available as PDF • Data for exercises and past examinations • Software: • SSORstat • PastiFit • PastiMos • Excel • …. any other, eg Splus, SAS, SPSS, Matlab wi2144st

16. Where, what • VSSD • A Modern Introduction to Probability and Statistics by • Dekking et al, ISBN 1-85233-896-2 • Computer rooms • Data for exercises and past examinations • Software: SSORstat, PastiFit, PastiMos and Excel • Web page: http://dutiosc.twi.tudelft.nl/~a90 (also via BB page) • Data for exercises and past examinations (zip-file) • Exercises and Examination Set (1994-2006) as pdf • Lecture notes Statistiek van Proefopzetten as pdf • Download software: SSORstat, PastiFit, PastiMos • And of course e-mail to the lecturers: • L.E.Meester@tudelft.nl, P.J.T.Verheijen@tudelft.nl wi2144st

17. Course Material and Information Changes with respect to 2005/2006 Lecture notes: Statistiek van proefopzetten ONLY available as pdf on website. Exercises and Examination Set: minor updates and inclusion of exams 2004/2005; ONLY available as pdf on website. wi2144st

18. Timetable • Course schedule 3rd period Room B • Thursday: hour 1+2 Lectures (/Exercises) • Friday: hour 5+6+7 Lectures/(Computer) Exercises • Course schedule 4th period Room B • Wednesday: hour 2+3+4 Lectures/(Computer) Exercises • Thursday: hour 3+4 Lectures/Exercises • Examination schedule • Full course examination: Thu., June 14, 14-17 • Full course examination: Tue., August 28, 14-17 wi2144st

19. Examination Material present: • Computer with • SSORstat • PastiFit • PastiMos • Excel • Formulas (from appendices Lecture Notes) Allowed: normal calculator wi2144st

20. Examination wi2144st

21. …. or ‘’Chance favors the prepared mind!’’ …. or “Het toeval begunstigt de voorbereide geest’’ … and what else Dans le domaine de la science, le hasard ne favorise que les esprits qui ont été préparés. Louis Pasteur, 1822-1895 wi2144st