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In null-hypothesis significance testing, the p-value is the probability of obtaining test results at least as extreme as the result actually observed, under the assumption that the null hypothesis is correct. A very small p-value means that such an extreme observed outcome would be very unlikely under the null hypothesis. Even though reporting p-values…
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hypothesis null test distribution p-values displaystyle probability significance statistical statistic heads data one 05 would tests coin level extreme value
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| P-value | is a | probability of obtaining test results at least as extreme as the result actually observed | 0.90 | text |
| P-value | is a | probability under the null hypothesis of obtaining a real-valued test statistic at least as extreme as the one obtained | 0.90 | text |
| P-value | is a | function of the chosen test statistic T | 0.90 | text |
| P-value | related to Definition | The | 0.60 | section |
| P-value | related to Definition | Consider | 0.60 | section |
| P-value | related to Definition | Then | 0.60 | section |
| P-value | related to Definition | That | 0.60 | section |
| P-value | related to Definition | Pr | 0.60 | section |
| P-value | related to Definition | If | 0.60 | section |
| P-value | related to Distribution | The | 0.60 | section |
| P-value | related to Distribution | If | 0.60 | section |
| P-value | related to Distribution | Regardless | 0.60 | section |
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