Data considerations for Individual Distribution Identification

To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.

The data should be continuous
Continuous data are measurements that may potentially take on any numeric value within a range of values along a continuous scale, including fractional or decimal values. Common examples include measurements such as length, weight, and temperature.
The sample data should be selected randomly
In statistics, random samples are used to make generalizations, or inferences, about a population. If your data were not collected randomly, your results may not represent the population.
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