In the Caucasus We Count
- Research
- Training


CRRC organizes training courses, seminars and lectures on a variety of social science topics, attracting both local and foreign experts as speakers or trainers, locally and regionally.

Methodological trainings and lectures

The CRRC methodological trainings focus on modernizing the skill sets of local researchers and providing hands-on opportunities in using relevant statistical software packages. These programs help strengthen research production and promote direct examination of what is really happening in today’s economic and social transformation in the South Caucasus.

Orientation trainings

CRRC also conducts basic orientation trainings to explore the range of research resource materials provided by the center and introduce effective methods of their use.

Conferences and roundtables

CRRC draws researchers, public administrators, and other policy practitioners from all three South Caucasus countries to discuss and debate on key public policy issues in the region and cross-border trends in policy formation, encouraging interdisciplinary dialogue among researchers and practitioners. The center provides information and educational assistance to emerging public policy institutes, and providing a variety of networking opportunities for researchers and policy practitioners. 

Other Trainings

Training on research skills and methods

Series of trainings on research skills and methods includes seminars/workshops on quantitative and qualitative research methods and data analysis. It is compiled of the following sessions:

1. Introduction: types of research, advantages, disadvantages
2. Research design (sampling/weights)
3. Focus groups
4. Questionnaire design
5. Easy statistics/SPSS (two sessions)
6. Presentations (presenting data; charts).

Training on using SPSS and Caucasus Barometer databases

The training consists of introduction to the statistical program SPSS and its main functions. It teaches how to retrieve CRRC's data through SPSS and make analysis. As Caucasus Barometer touches upon a broad scope of topics and information on the population, it can be useful for different aspects of research, such as attitudes to politics and democratic processes, economic conditions, religious beliefs, health issues, social networks.

Sample Design and Data Analysis

The sample design and data analysis course focuses on the analysis of data from complex surveys such as those conducted by CRRC, and also on the design of such surveys. While many local professionals have education in basic statistics, these skills only allow researchers to work with simple random samples. Due to the realities of surveying people and the constraints under which research organizations such as CRRC operate, simple random sampling is unfeasible and complex survey designs are required. However, training in complex survey design has not previously been available in Tbilisi. Thus, in the past, sample design and key data analysis components have generally been outsourced. The main goals of this course are to enable participants to analyze the data collected in complex surveys such as CRRC's Caucasus Barometer and to design such surveys. The larger objective is to build research capacity within CRRC and other local organizations. 

The major topics covered in the course include (i) simple random sampling, (ii) stratified sampling, (iii) cluster sampling, and (iv) complex sampling.
i. The simple random sampling topic includes a focus on simple probability sampling, sampling distributions, estimation of population parameters from samples, and required sample size calculations. 
ii. The stratified sampling topic includes the motivation for stratification, the design of stratified samples, and the estimation of population parameters from stratified samples. 
iii. The cluster sampling topic includes the various types of cluster sampling, the motivation for cluster sampling, the design of cluster samples, and the estimation of population parameters from cluster samples. 
iv. The complex sampling topic involves the integration of the concepts learned in the first three topics, as complex surveys are designed using combinations of simple random, stratified, and cluster sampling. The topic includes the estimation of population parameters from complex surveys and complex survey design.