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GRD for R: An intuitive tool for generating random data in R

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Doi: 10.20982/tqmp.15.1.p001

Calderini, Matias , Harding, Bradley
Keywords: Statistics Teaching; Data Simulations; Sampling; R
(no sample data)   (Appendix)

Statistics courses prove to be a common difficulty to many social sciences students. To address this problem, we developed a tool in the R programming language \parencite {R18} that can be used to easily and quickly generate data to be analysed. The Generator of Random Data or GRD, allows the user to build datasets according to any design type, both within and between, with or without statistical effects and/or correlations. By default, GRD creates normally distributed data, but any type of distribution defined in R can be specified. With GRD, it is possible to generate samples of any size and see the benefit of larger sample sizes on the precision of statistical measures. The students of statistics can acquire better skills in analyzing custom-made datasets, skipping long data-acquisition processes. They can also experience first-hand concepts such as statistical power and type-I and type-II errors. Each sample being different, students can appreciate randomness at the tips of their fingers.

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