
To master statistics and data analysis tools, it is necessary to understand a number of concepts, manyof which are quite abstract. For example, sampling from a theoretical distribution can help individuals explore andunderstand randomness. Sampling can also be used to build exercises aimed to help students master statistics. Here, we present GRD (Generator of Random Data), an extension command for SPSS (version 17 and above). With GRD, it is possible to get random data from a given distribution. In its simplest use, GRD will return a set of simulated data from a normal distribution.With subcommands to GRD, it is possible to get data from multiple groups, over multiple repeated measures, and with desired effectsizes. Group sizes can be equal or unequal. With further subcommands, it is possible to sample from any theoretical population, (not simply the normal distribution), introduce non-homogeneous variances,fix or randomize subject effects, etc. Finally, GRD’s generated data are in a format ready to be analyzed.
Data Simulations, Psychology, Statistics Teaching, Sampling, SPSS, BF1-990
Data Simulations, Psychology, Statistics Teaching, Sampling, SPSS, BF1-990
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 8 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
