Lesson plan
King effect
except in the cases of the two "kings": China and India. The king effect is the name given by Jean Laherrère and Didier Sornette to the phenomenon in natural distributions where the top one or two members of a ranked set are clear outliers. These top one or two members are unexpectedly large and do not conform to the statistical distribution or rank-distribution which the remainder of the set follows. Distributions typically followed include the power-law distribution, that is a basis for the stretched exponential function, and parabolic fractal distribution. Laherrere and Sornette noted the King effect in the distributions of: * French city sizes (where the point representing Paris is the "king", failing to conform to the stretched exponential ), and similarly for other countries with a primate city, such as the United Kingdom (London), and the extreme case of Bangkok (see list of cities in Thailand). * Country populations (where only the points representing China and India fail to fit a stretched exponential ). Note, however, that the king effect is not limited to outliers with a positive evaluation attached to their rank: for rankings on an undesirable attribute, there may exist a pauper effect, with a similar detachment of extremely ranked data points from the reasonably distributed portion of the data set.
Article summary
except in the cases of the two "kings": China and India. The king effect is the name given by Jean Laherrère and Didier Sornette to the phenomenon in natural distributions where the top one or two members of a ranked set are clear outliers. These top one or two members are unexpectedly large and do not conform to the statistical distribution or rank-distribution which the remainder of the set follows. Distributions typically followed include the power-law distribution, that is a basis for the stretched exponential function, and parabolic fractal distribution. Laherrere and Sornette noted the King effect in the distributions of: * French city sizes (where the point representing Paris is the "king", failing to conform to the stretched exponential ), and similarly for other countries with a primate city, such as the United Kingdom (London), and the extreme case of Bangkok (see list of cities in Thailand). * Country populations (where only the points representing China and India fail to fit a stretched exponential ). Note, however, that the king effect is not limited to outliers with a positive evaluation attached to their rank: for rankings on an undesirable attribute, there may exist a pauper effect, with a similar detachment of extremely ranked data points from the reasonably distributed portion of the data set.
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.