The R-STAT Statistics Laboratory provides statistical analyses of various sophistication level. We apply statistical methods in all fields of science: Economy, Psychology, Sociology, Medicine, Political Science, Technical Sciences. Our aim is to help the research community in investigations that have a non trivial statistics content. We enter into relations with scientists, institutions and companies who use statistical methods in their activity.
We divide our activity into parts:
We divide our activity into parts:
- Consulting in the field of statistics (and all fields related to statistics)
- Clinical research, BioStatistics, medicine-promoting surveys.
- Data analyses.
We take part in all stages of the research project, including:
- Experimental design
- CRF design
- Questionnaire analysis and questionnaire design
- Sample size, choice of randomization methods
- Data entry, electronic database
- Data description and analysis (establishing hypotheses)
- Statistical reports and presentations
- statistical training
- Consultation in the field of statistical software.
The R-STAT Statistics Laboratory consult problems in all fields related to statistics:
- Descriptive Statistics
- Mathematical Statistics
- Econometrics
- Forecasting process and data analysis, Time series analysis
- Psychometrics
- Applied Mathematics (Mathematical modeling).
To assume, we support our Clients at the all stages of a research, we give our Clients expert advices and professional consultations. Consulting can be done in many ways - from a meeting or two on a specific problem, to a full cooperation on a research project from the design to the final analysis. Another possible mode of work is cooperation with a scientist, which may end up in a joint publication. The statistical methods can be standard. Our main interest, however, is in the application of non-standard and advanced data analysis methodologies.
If anyone has any doubt about the great impact of statistics on other sciences we cite the following statements:
“Until the phenomena of any branch of knowledge have been subjected to measurement and number, it cannot assume the status and dignity of a science” (Galton, 1879, p. 149)
“When you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind” (Kelvin, 3 May 1883, as cited in Thompson, 1910/1976)
Zadeh (2000) notes how the privileged position of numbers is less obvious with the advent of powerful computers for dealing with non-numeric data.