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Individual Distribution IdentificationData Fitted with 14 Distributions and 2 Transformations - Table of Percentiles |
The percentile for P percent is the value below which you expect P percent of the population values to fall. Sometimes it can be difficult to determine the best distribution based on the probability plot and goodness-of-fit measures. Use the table of percentiles for several selected distributions to see how your conclusions change depending on the distribution chosen.
Example Output |
Table of Percentiles
Standard Distribution Percent Percentiles Error 95.0% CI Normal 5 46.2344 0.60235 45.1 47.4 Box-Cox Transformation 5 0.0000 0.00000 0.0 0.0 Lognormal 5 46.4243 0.54293 45.4 47.5 3-Parameter Lognormal 5 47.2553 0.29629 46.7 47.8 Exponential 5 2.6048 0.36837 2.0 3.4 2-Parameter Exponential 5 46.9272 0.02947 46.9 47.0 Weibull 5 44.1343 0.93755 42.3 46.0 3-Parameter Weibull 5 47.2723 0.17351 46.9 47.6 Smallest Extreme Value 5 43.4339 1.11157 41.3 45.6 Largest Extreme Value 5 47.1229 0.35058 46.4 47.8 Gamma 5 46.4076 0.55357 45.3 47.5 3-Parameter Gamma 5 47.2157 0.24845 46.7 47.7 Logistic 5 45.8759 0.65347 44.6 47.2 Loglogistic 5 46.0949 0.59123 45.0 47.3 3-Parameter Loglogistic 5 47.2549 0.34441 46.6 47.9 Johnson Transformation 5 -1.5714 0.21197 -2.0 -1.2 |
Interpretation |
For 3-parameter Weibull and largest extreme value, two of the better fitting distributions, you can expect 5% of the calcium data to fall below 47.2723 and 47.1229. Depending on the context, this additional data may help you select the better distribution. For instance, if one value provided a larger margin of safety in your decision making you might select that distribution.
The values for the Box-Cox (0.0000) and Johnson (-1.5714) transformations are based on the transformed values rather than the raw data making the percentiles difficult to interpret.