Lesson plan
Beta regression
Beta regression is a form of regression which is used when the response variable, y , takes values within (0, 1) and can be assumed to follow a beta distribution. It is generalisable to variables which takes values in the arbitrary open interval (a, b) through transformations. Beta regression was developed in the early 2000s by two sets of statisticians: Kieschnick and McCullough in 2003 and Ferrari and Cribari-Neto in 2004.
Article summary
Beta regression is a form of regression which is used when the response variable, y , takes values within (0, 1) and can be assumed to follow a beta distribution. It is generalisable to variables which takes values in the arbitrary open interval (a, b) through transformations. Beta regression was developed in the early 2000s by two sets of statisticians: Kieschnick and McCullough in 2003 and Ferrari and Cribari-Neto in 2004.
Key claims
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Discussion questions
- Summarise the article in your own words. Which single claim would you verify first, and why?
- Which claim in this article is most likely to be revised as the sources update? How would you check its current status?
- If two sources disagreed about one of these facts, what would you need in order to trust one over the other?
Bibliography
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Key claims and bibliography are generated from the same tracked claims and sources as the article page.