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statistics

This category contains 6 posts

Include uncertainty in a financial model

Here’s a post that appears on my new website, coppelia.io. The problem You’ve been asked to calculate some figure or other (e.g. end of year revenue, average customer lifetime value) based on numbers supplied from various parts of the business. You know how to make the calculation but what bothers you is that some of … Continue reading

Freehand Diagrams with Adobe Ideas

Freehand diagrams have two big virtues: they are quick and they are unconstrained. I used to use a notebook (see What are degrees of freedom) but recently I got an ipad and then I found Adobe Ideas. It’s completely free and has just the right level of complexity for getting ideas down fast. It takes … Continue reading

Visualising Shrinkage

A useful property of mixed effects and Bayesian hierarchical models is that lower level estimates are shrunk towards the more stable estimates further up the hierarchy. To use a time honoured example you might be modelling the effect of a new teaching method on performance at the classroom level. Classes of 30 or so students … Continue reading

Book Recommendations from Beyond the Grave: A Mahout Example

In H P Lovecraft’s The Case of Charles Dexter Ward the villainous Curwen, having taken possession of the body of Charles Dexter Ward, uses a combination of chemistry and black magic to bring back from the dead the wisest people who have ever lived. He then tortures them for their secrets. Resurrection of the dead … Continue reading

What are degrees of freedom?

I remember getting frustrated as an undergraduate trying to find straight answer to this question. The standard text book answer is something like this: “In statistics, the number of degrees of freedom is the number of values in the final calculation of a statistic that are free to vary” That’s from Wikipedia but it’s fairly … Continue reading

Expected switching for the Dirichlet distribution

A valuable tool in choice modelling is the Dirichlet-multinomial distribution. It’s a compound of the multinomial and Dirichlet distributions and it works like this: A choice between N options is modelled as a multinomial distribution with parameters θ1, θ2, θ3 … θN, where the thetas also represent the probabilities of each option being chosen. For … Continue reading

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