Category Archives: Statistics

A look at Bayesian statistics

An introduction to Bayesian analysis and why you might care. Fight club The subject of statistics is about how to learn.  Given that it is about the unknown, it shouldn’t be surprising that there are deep differences of opinion on how to go about doing it (in spite of the stereotype that statisticians are accountants … Continue reading

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Exponential decay models

All models are wrong, some models are more wrong than others. The streetlight model Exponential decay models are quite common.  But why? One reason a model might be popular is that it contains a reasonable approximation to the mechanism that generates the data.  That is seriously unlikely in this case. When it is dark and … Continue reading

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Information flows like water

Guiding a ship, it takes more than your skill Spark David Rowe’s Risk column this month is about data leverage. The idea is that you are leveraging your data if you are using it to answer questions that are too demanding of information. The piece reminded me of a talk that Dave gave a few … Continue reading

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The US market will absolutely positively definitely go up in 2012

The Super Bowl tells us so. The Super Bowl Indicator The championship of American football decides the direction of the US stock market for  the year.  If a “National” team wins, the market goes up; if an “American” team wins, the market goes down. Yesterday the Giants, a National team, beat the Patriots. The birth … Continue reading

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Things I learned at useR!2011

The title says “things” but conferences are mainly about people. Some of it can be serendipitous.  For example, one day I sat next to Jonathan Rougier at lunch because I had a question for him about climate models.  When Jonathan left, I started a conversation with the person on my other side.  That was most … Continue reading

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Winsorization replaces extreme data values with less extreme values. But why Extreme values sometimes have a big effect on statistical operations.  That effect is not necessarily a good effect.  One approach to the problem is to change the statistical operation — this is the field of robust statistics. An alternative solution is to just change … Continue reading

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Blog year 2010 in review

The blog year started in August and consists of 30-something posts.  Here is a summary. Most popular Ideas for World Statistics Day A quant review of “The Quants” by Scott Patterson A tale of two returns The tightrope of the random walk What the hell is a variance matrix? Most under-valued Most read is not … Continue reading

Posted in Blog, Book review, Fund management in general, Quant finance, R language, Risk, Statistics | Tagged , , | 8 Comments

Joy of Stats coming soon

The Joy of Stats really is a joy.  It will be shown on BBC4, apparently scheduled for December 7.  (That date comes from Hans Rosling on twitter, I haven’t found scheduling evidence at the BBC.) I saw its debut at the Royal Statistical Society on World Statistics Day. Here is a five minute excerpt: You … Continue reading

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Yet another inferno

Many from the R world will know The R Inferno. Abstract: If you are using R and you think you’re in hell, this is a map for you. A newly minted inferno is The 9 circles of scientific hell. Most amusing to me is Circle 4: p-value fishing, the punishment of which is brilliant. As … Continue reading

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R is a name you need to know

As if that is news to some of you. Forbes has a Mean Business blog post by Steve McNally titled “Names You Need to Know in 2011: R Data Analysis Software”. The post includes several links to why R is wonderful. It also includes a pretty — but seemingly useless — statistical graph.  Correct me … Continue reading

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