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In statistics, the Behrens–Fisher problem, named after Walter-Ulrich Behrens and Ronald Fisher, is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples.
Welch's approximate t solution, Behrens and Fisher approach & Generalisations
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| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Behrens–Fisher problem | related to Context | Let X1 | 0.60 | section |
| Behrens–Fisher problem | related to Context | Xn | 0.60 | section |
| Behrens–Fisher problem | related to Context | Y1 | 0.60 | section |
| Behrens–Fisher problem | related to Context | Ym | 0.60 | section |
| Behrens–Fisher problem | related to Context | The | 0.60 | section |
| Behrens–Fisher problem | related to Context | Lehmann | 0.60 | section |
| Behrens–Fisher problem | related to Context | Behrens | 0.60 | section |
| Behrens–Fisher problem | related to Context | Fisher | 0.60 | section |
| Behrens–Fisher problem | related to Context | While Lehmann | 0.60 | section |
| Behrens–Fisher problem | related to Exact solutions to the common and generalized Behrens–Fisher problems | For | 0.60 | section |
| Behrens–Fisher problem | related to Exact solutions to the common and generalized Behrens–Fisher problems | Behrens | 0.60 | section |
| Behrens–Fisher problem | related to Exact solutions to the common and generalized Behrens–Fisher problems | Fisher | 0.60 | section |
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