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In statistics, overdispersion is the presence of greater variability (statistical dispersion) in a data set than would be expected based on a given statistical model.
Products, Examples & Differences in terminology among disciplines
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model distribution data variance normal binomial fit expected mean poisson parameter random given empirical parameters higher theoretical one free example
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Overdispersion | is a | presence of greater variability | 0.90 | text |
| Overdispersion | is a | very common feature in applied data analysis because in practice | 0.90 | text |
| Overdispersion | is a | feature | 0.90 | text |
| Overdispersion | related to Differences in terminology among disciplines | Over | 0.60 | section |
| Overdispersion | related to Differences in terminology among disciplines | In | 0.60 | section |
| Overdispersion | related to Differences in terminology among disciplines | This | 0.60 | section |
| Overdispersion | related to Differences in terminology among disciplines | Such | 0.60 | section |
| Overdispersion | related to Differences in terminology among disciplines | Generally | 0.60 | section |
| Overdispersion | related to Poisson | Poisson | 0.60 | section |
| Overdispersion | related to Poisson | The Poisson | 0.60 | section |
| Overdispersion | related to Poisson | The | 0.60 | section |
| Overdispersion | related to Poisson | For | 0.60 | section |
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