0409 Statistics for Economics and Social Sciences with R
Annalisa Cadonna, Ph.D.
Language of instruction
09/17/19 to 09/24/19
Registration via LPIS
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
|Wednesday||10/02/19||02:00 PM - 04:00 PM||TC.3.02|
|Wednesday||10/09/19||02:00 PM - 04:00 PM||TC.-1.61|
|Wednesday||10/16/19||02:00 PM - 04:00 PM||LC.2.064 Raiffeisen Kurslabor|
|Wednesday||10/23/19||02:00 PM - 04:00 PM||LC.2.064 Raiffeisen Kurslabor|
|Wednesday||10/30/19||02:00 PM - 04:00 PM||TC.-1.61|
|Wednesday||11/06/19||02:30 PM - 04:30 PM||TC.-1.61|
|Wednesday||11/13/19||02:00 PM - 04:00 PM||LC.-1.038|
|Wednesday||11/20/19||02:00 PM - 04:00 PM||LC.2.064 Raiffeisen Kurslabor|
|Wednesday||11/27/19||02:00 PM - 04:00 PM||LC.-1.038|
|Wednesday||12/04/19||03:00 PM - 05:00 PM||LC.-1.038|
|Wednesday||12/11/19||02:00 PM - 04:00 PM||LC.-1.038|
|Wednesday||12/18/19||02:00 PM - 04:00 PM||LC.-1.038|
- Introduction to R
- Descriptive statistics and graphs:
- Measures of center(average, median, ...)
- Measures ofdispersion (variance, standard deviation, ...)
- Histogram, density plot
- Bar plot, spineplot, mosaic plot
- Box plot
- Association (correlation,Pearson & Spearman)
- Statistical inference:
- Chi-squared tests
- Odds Ratios
- (Binary) logistic regression
- Dummyvariabels for categorial predictors
- (Univariate) simple and multiple linear regression
- T-test and simple analysis of variance
- Mann-Whitney U-Test and Kruskal-Wallis H test
- Analysis of Variance (ANOVA)
In this course, you will learn basic statistical techniques widely used in econometrics and economics. All presented methods are illustrated with practical examples to provide you with the tools to carry out statistical analysis using the software R.
For this lecture participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).
The course is held weekly. The subject is presented by the lecturer in theoretical units and illustrated with data sets. The performance of the students is assessed through various exercises and a test (see Assesment).
- No more than 2 absences.
- Quizzes: 5 best out 6 (10 points total, 2 points per quiz)
- Homework: 10 exercises (50 points, each exercise is worth 5 points).
- Multiple choice final exam (20 points).
- Of the 80 total points, at least 70% must be achieved for a positive score.
- Active participation in the computer exercises (8 bonus points for cooperation possible).
Last edited: 2019-03-20