Gaussian distribution; Normal curve; Normal distribution
A normal distribution of observations/scores is shaped like a “bell,” with the majority of observations/scores occurring around the mean and increasingly fewer observations/scores occurring farther (above/below) from the mean (68.26% of observations/scores fall within one standard deviation of the mean; 95.44% fall within two standard deviations of the mean). A normal distribution of observations is typical in large samples acting additively and independently and is assumed in parametric statistics (e.g., t-tests, ANOVA). Standardized scores derived from neuropsychological measures are based upon (assume) normal distribution of the standardization sample. While this assumption provides a common metric that allows for direct comparison of performance between different measures, it is important to note that score distributions for a number of neuropsychological tests are non-normal (e.g., Boston Naming Test,...
References and Readings
- Lezak, M. D., Howieson, D. B., Bigler, E. D., & Tranel, D. (2012). Neuropsychological assessment (5th ed.). New York: Oxford University Press.Google Scholar
- Sattler, J. M. (2001). Assessment of children: Cognitive foundations (5th ed.). La Mesa: Jerome M. Sattler.Google Scholar
- Strauss, E., Sherman, E. M. S., & Spreen, O. (2006). A compendium of neuropsychological tests: Administration, norms, and commentary (3rd ed., pp. 3–43). New York: Oxford University Press.Google Scholar