Weibull++ Simumatic Data 1P-Weibull: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
| Line 12: | Line 12: | ||
|- | |- | ||
| valign="middle" | | | valign="middle" | | ||
Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to | Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to a) better understand life data analysis concepts, b) experiment with the influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand the concepts behind confidence intervals and e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with SimuMatic utility in Weibull++. | ||
a) better understand life data analysis concepts, | |||
b) experiment with the influences of sample sizes and censoring schemes on analysis methods, | |||
c) construct simulation-based confidence intervals, | |||
d) better understand the concepts behind confidence intervals and | |||
e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with SimuMatic utility in Weibull++. | |||
|- | |- | ||
Revision as of 17:20, 10 February 2012
 |
| Simumatic Data 1P Weibull |
| Weibull++ |
|
Reliability analysis using simulation, in which reliability analyses are performed a large number of times on data sets that have been created using Monte Carlo simulation, can be a valuable tool for reliability practitioners. Such simulation analyses can assist the analyst to a) better understand life data analysis concepts, b) experiment with the influences of sample sizes and censoring schemes on analysis methods, c) construct simulation-based confidence intervals, d) better understand the concepts behind confidence intervals and e) design reliability tests. This section explores some of the results that can be obtained from simulation analyses with SimuMatic utility in Weibull++. |
| See an example... |