TY - JOUR
AU - Jake Olivier
AU - Melissa M. Norberg
PY - 2010/06/30
Y2 - 2020/10/22
TI - Positively skewed data: revisiting the box-cox power transformation.
JF - International Journal of Psychological Research
JA - IJPR
VL - 3
IS - 1
SE - Research Article
DO - 10.21500/20112084.846
UR - https://revistas.usb.edu.co/index.php/IJPR/article/view/846
AB - Although the normal probability distribution is the cornerstone of applying statistical methodology; data do not always meet the necessary normal distribution assumptions. In these cases, researchers often transform non-normal data to a distribution that is approximately normal. Power transformations constitute a family of transformations, which include logarithmic and fractional exponent transforms. The Box-Cox method offers a simple method for choosing the most appropriate power transformation. Another option for data that is positively skewed, often used when measuring reaction times, is the Ex-Gaussian distribution which is a combination of the exponential and normal distributions. In this paper, the Box-Cox power transformation and Ex-Gaussian distribution will be discussed and compared in the context of positively skewed data. This discussion will demonstrate that the Box-Cox power transformation is simpler to apply and easier to interpret than the Ex-Gaussian distribution.
ER -