In parametric biostatistics tests, data is defined as normally distributed if it meets which criteria?

In parametric biostatistics tests, one of the primary criteria for data to be considered normally distributed is that the mean, median, and mode are all equal. This characteristic indicates that the data is symmetrically distributed around the central value, which is a defining feature of a normal distribution. In a perfectly normal distribution, the three measures of central tendency coincide at the same point.

Other characteristics, while they may be related to the concept of normality, do not fundamentally define whether data is normally distributed. For instance, the concept of skewness, which pertains to the asymmetry of the distribution, is intrinsically linked to the equality of the mean, median, and mode. If there is no skew, that typically means the data is symmetrically distributed, further supporting the idea of equal central tendencies, but it is not a stand-alone condition for normality.

Data being discrete refers to the type of data rather than its distribution. Discrete data can be normally distributed if it meets the necessary criteria, but it does not inherently imply normality. Therefore, while it is an important consideration in data analysis, it does not serve as a defining characteristic of a normal distribution.

Thus, the correct answer focuses specifically on the equality of the mean