This course provides an introduction to the statistical programming language R. Since R has gained a lot of attention among data analysts in general and social scientists in particular, we will emphasize the particularities of survey data analysis using R. The objective of the course is to enable attendants to write their own project syntax ranging from importing data into R to applying standard and more advanced analysis methods. We expect participants to be already familiar with data analysis in general and ideally with some other statistical analysis software such as Stata or SPSS.Because the course is introductory with respect to R and not statistics, we will not cover introduction to basic statistical methods (see course prerequisites).The course also aims to help those interested in attending the course %E2%80%9CItem nonresponse and multiple imputation%E2%80%9D or/and %E2%80%9CSampling, Weighting and Estimation%E2%80%9D acquire a sufficient level of R knowledge.

Course leader
Hans Walter Steinhauer, Ariane Wrbach

Target group
Participants will find the course useful if they:- want to benefit from recent implementations of statistical algorithms and methods;- have to do a lot of data analysis, and create graphics or (standardized) reports;- need a powerful tool at hand for various tasks;- want to become part of a fast-growing user community;- have been wondering if R is hard to learn (No, it is not!);- wish to acquire sufficient knowledge of R language for the course "Item nonresponse and multiple imputation" or/and "Sampling, Weighting and Estimation."Prerequisites:- (ideally) prior experience with statistical software;- prior experience with data analysis;- familiarity with introductory statistical methods;- familiarity with the (generalized) linear model;- basic concept of matrix algebra recommended.

Course aim
By the end of the course participants will:- be able to conduct sophisticated (survey) data analysis in R;- know how to create publishable graphics and tables;- be familiar with "programming" statistical analysis;- be able to structure workflow in research projects.

Credits info
4 ECTS - Certificate of attendance issued upon completion.Optional bookings:- 2 ECTS points via the University of Mannheim for regular attendance and satisfactory work on daily assignments (EUR 20).- 4 ECTS points via the University of Mannheim for regular attendance and satisfactory work on daily assignments and for submitting a paper/report of about 5000 words to the lecturer(s) up to 4 weeks after the end of the summer school (EUR 50).

Fee info
EUR 250: Student/PhD student rate. EUR 350: Academic/non-profit rate.Early bird discount: EUR 50 for applicants who book and pay by April 30.The rates include the tuition fee, course materials, the academic program, access to library and IT facilities, coffee/tea, and a number of social activities.

Scholarships
10 DAAD scholarships are available via the Center for Doctoral Studies in Social and Behavioral Sciences (CDSS) at the University of Mannheim.

GESIS-Leibniz Institute for the Social Sciences
Address: Knowledge Transfer, Unter Sachsenhausen 6-8 Cologne
Postal code: 50667
City: Cologne
Country: Germany
Website: http://www.gesis.org/summerschool
E-mail: summerschool@gesis.org
Phone: +49-221-476940