Adjusted R-square
Analysing qualitative data.
Analysing quantitative data
ANCOVA (Analyses of covariance)
ANOVA (Analyses of variance)
Applied research
Average
Bias
[...]
Generating data
Sometimes data are generated. That is the case when scientists conduct a simulation study. The data are withdrawn (generated) from a fictional reality.
Usually in research data are withdrawn from the empery. In a simulation, however, the data is not collected from reality but is generated by a programme. The data produced is stored in a database and this is used for making analysis.
What makes generating data so special?
Generating data is one out five methods for gathering data to fill a database. The other four are observing, interviewing, measuring, and copy and transferring data. Every method is described separately. On this page we pay attention to generating data.
Compared to any other kind of research, the data are not collected from a fictional reality. Several fictional realities can be produced and from each reality data can be withdrawn. With these data all kinds of research can be done. See for more information about this topic our page about simulation.
The quality of the data
Validity and reliability are important aspects of the simulation model when generating data. If the model is wrong, valid or reliable data cannot be generated. However, this is not that important. Usually the data is used for a fictional reality in the future or from the past. The generated data is only used for describing and comparing situations that usually will not become real.
Even though the simulated realities will never come true, it is a good method for experimental research. It is helpful to predict the future by making different decisions in the present.
