Statistics for Experimental Economists SS 2007This course is part of the International Max Planck Research School on Adapting Behavior in a Fundamentally Uncertain World. The target group are students who, due to the interdisciplinary nature of the IMPRS school, do not have any background in statistics
- Lecture (daily): 13.8.-17.8., 8:15-9:45, 14:15-14:45
- Elementary Probability Calculus
- Random Variables
- Stochastic Models and Distributions
- Limit Theorems
- Point Estimation
- Estimation of Intervals
- Basic Statistical Tests
- OLS Regression
- Maximum Likelihood (if time permits)
- Choice Models (if time permits)
- Censored Models (if time permits)
- For our practical examples (during the entire course) we will use the software environment R. I think that it is helpful to coordinate on one environment and R has the advantage of being free and rather powerful.
- Documentation for R is
provided via the built in help system but also through the
- The R Guide, Jason Owen (Easy to read, tries to explain R with the help of examples from basic statistics)
- Simple R, John Verzani (Tries to explain R with the help of examples from basic statistics)
- Einführung in R, Günther Sawitzki (In German. Rather compact introduction. The statistical part can be quite demanding)
- Econometrics in R, Grant V. Farnsworth (The introduction to R is rather compact and pragmatic. The econometric models go beyond what we are doing in this lecture)
- An Introduction to R, W. N. Venables und D. M. Smith (The focus is more on R as a programming language)
- The R language definition (Concentrates only on R as a programming language. A must to read if you write your own functions)
- A first entry into R eased through mice and menues is available through the R Commander.
- An interesting development environment is RStudio.
- In the lecture I use the versatile editor Emacs with the ESS interface (ESS also helps with Stata, SAS, Splus, BUGS, and others). Users of MacOS-X will prefer the Emacs-Clone aquamacs.
- Documentation for R is provided via the built in help system but also through the R Homepage. Useful are
- Handout + Exam
- The handout will be updated a few times. Data is also attached to the handout. If you wish you can have a look at the exam. I have added some notes that might help you in finding a solution.
- Stock and Watson; Introduction to Econometrics; 2nd Edition; Pearson 2006.
- Michael Murray; Econometrics, a Modern Introduction; Pearson 2006
- William Greene, Econometric Analysis, Prentice Hall, 6th Edition, 2003.
- Christian Gourieroux and Alain Monfort, Statistics and Econometric Models, Vol. 1, Cambridge, 1995.