The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Skewness and Kurtosis in Real Data Samples
Abstract
Parametric statistics are based on the assumption of normality. Recent findings suggest that Type I error and power can be adversely affected when data are non-normal. This paper aims to assess the distributional shape of real data by examining the values of the third and fourth central moments as a measurement of skewness and kurtosis in small samples. The analysis concerned 693 distributions with a sample size ranging from 10 to 30. Measures of cognitive ability and of other psychological variables were included. The results showed that skewness ranged between −2.49 and 2.33. The values of kurtosis ranged between −1.92 and 7.41. Considering skewness and kurtosis together the results indicated that only 5.5% of distributions were close to expected values under normality. Although extreme contamination does not seem to be very frequent, the findings are consistent with previous research suggesting that normality is not the rule with real data.
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Cites
Glass, G. V., Peckham, P. D., & Sanders, J. R. (1972) · Review of Educational Research · doi:10.3102/00346543042003237 · Cited by 1,826
Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy
Wilcox, R. R. (2010) · doi:10.1007/978-1-4419-5525-8 · Cited by 404
Cited by
Non-normal data: Is ANOVA still a valid option?
Blanca, M., Alarcón, R., Arnau, J., Bono, R., & Bendayan, R. (2017) · Psicothema · doi:10.7334/psicothema2016.383 · Cited by 1,624
“Distributions with a slight and moderate degree of contamination (Blanca et al., 2013) were simulated by generating distributions with values of skewness and kurtosis ranging between -1 and 1.”
Self-citationde Winter, J. C. F., Gosling, S. D., & Potter, J. (2016) · Psychological Methods · doi:10.1037/met0000079 · Cited by 1,201
Research Design in Clinical Psychology
Kazdin, A. E. (2021) · doi:10.1017/9781108993647 · Cited by 240
Sato, M., & Loewen, S. (2018) · Language Learning · doi:10.1111/lang.12283 · Cited by 195
Majeed, M., Irshad, M., Fatima, T., Khan, J., & Hassan, M. M. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.557987 · Cited by 73
Metadata
- Authors
- Blanca, M. J., Arnau, J., López-Montiel, D., Bono, R., & Bendayan, R.
- Venue
- Methodology
- Publisher
- Hogrefe Publishing Group
- Published
- 2013-05-01
- Volume
- 9
- Issue
- 2
- Pages
- 78-84
- ISSN
- 1614-1881 (ISSN-L)
- 1614-2241
- OpenAlex
- W2162503628
- Cited by
- 479
- References
- 2
- FWCI
- 8.09
- Type
- journal article
- Language
- en
- Open access
- closed
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- Blanca, M. J., Arnau, J., López-Montiel, D., Bono, R., & Bendayan, R. (2013). Skewness and Kurtosis in Real Data Samples. Methodology. https://doi.org/10.1027/1614-2241/a000057
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
