Resumen
Este artículo metodológico tiene como objetivo exponer la Ley de Newcomb-Benford de una forma clara, acompañada de un ejemplo, para facilitar su comprensión entre diversas áreas de investigación psicológica ajenas a su uso en otras disciplinas, incluida la ciencia cognitiva. Se aplica sobre todo a la detección del fraude en bases de datos y escrutinio electoral. Este artículo inicia con una reseña histórica, presenta las distribuciones del primer al cuarto dígito significativo y la de dos dígitos. Se revisan las explicaciones estadístico-matemáticas de la ley. Se presentan de forma aplicada seis pruebas de bondad de ajuste y el cálculo de intervalos de confianza simultáneos para comprobar el cumplimiento de la ley. Se usan datos simulados que siguen dos distribuciones: normal y lognormal. La primera, común en psicología, no se ajusta a la ley, mientras que la segunda posibilita transformar la distribución normal para cumplirla. Finalmente, se extraen conclusiones y se plantean sugerencias para detectar manipulación de datos normalmente distribuidos.
Citas
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