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Getting the most from your curves: Exploring and reporting data using informative graphical techniques

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Doi: 10.20982/tqmp.05.2.p040

Marmolejo-Ramos, Fernando , Matsunaga, Masaki
Keywords: Statistics , Exploratory data analysis , Box plot , Confidence intervals , Violin plot
Tools: R
(no sample data)   (Appendix)

Most psychological research employs tables to report descriptive and inferential statistics. Unfortunately, those tables often misrepresent critical information on the shape and variability of the data’s distribution. In addition, certain information such as the modality and score probability density is hard to report succinctly in tables and, indeed, not reported typically in published research. This paper discusses the importance of using graphical techniques not only to explore data but also to report it effectively. In so doing, the role of exploratory data analysis in detecting Type I and Type II errors is considered. A small data set resembling a Type II error is simulated to demonstrate this procedure, using a conventional parametric test. A potential analysis routine to explore data is also presented. The paper proposes that essential summary statistics and information about the shape and variability of data should be reported via graphical techniques.

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