The parameter estimates define the best-fitting parameter estimates for the distribution that you select. All other parametric distribution analysis graphs and statistics are based on the distribution. Therefore, to obtain accurate estimates, the distribution that you select for the analysis must adequately fit the data.
You cannot determine from the estimated distribution parameters whether the distribution that you selected fits the data well. Use the distribution ID plot, probability plot, and goodness-of-fit measures to determine whether the distribution adequately fits the data.
Standard Error | 95.0% Normal CI | |||
---|---|---|---|---|
Parameter | Estimate | Lower | Upper | |
Location | 4.09267 | 0.0719681 | 3.95161 | 4.23372 |
Scale | 0.486216 | 0.0606247 | 0.380799 | 0.620816 |
For the engine windings data, the engineer selected a lognormal distribution. For the temperature of 80° C, the location and scale parameters that define the best-fitting lognormal distribution are location = 4.09267 and scale = 0.486216.