Category Archives: Pystan

Scientific Gambling – how do betting shops make money….?

Betting shops are commercial businesses, that is, they want to and must make money in order to survive. Like any other business. So take a casino as an example: they make money – in the long run – by having … Continue reading

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Prognos Val2018 – Bayesian Inference

Uppdaterat prognosen för Riksdagsvalet 2018 med februari-datat från samtliga opinionsinstitut. Mest noterbart är att KD med 75% sannolikhet ramlar ur Riksdagen.  Övriga partier befinner sig utanför riskzonen att ramla ur.

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Val 2018 – KD ramlar ur Riksdagen

Har nu uppdaterat både datat och min Bayesian Inferencemodell, datat genom att lägga till siffrorna från samtliga övriga opinionsinstitut, och modellen körs numera i Stan, ett domänspecifikt språk för statistiska analyser. Efter en körning av samtliga publicerade opinionsundersökningar sedan valet … Continue reading

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Bayesian A/B-testing, part III

This final part on Bayesian A/B-testing will continue looking at the various assumptions, implicit or explicit, that always are in play when building statistical models.  In part II, we looked at what impact larger data sets have on our inferences, … Continue reading

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Bayesian A/B-testing, part II

Continuing my example by examining how the different assumptions – yes, in any model there are always assumptions, explicit or implicit – of the model impact the end result, that is, the prediction of the sought after signup-rate, a.k.a our posterior … Continue reading

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A/B-testing with Bayesian Inference

The example Inspired by Rasmus Bååth’s lectures on Bayesian Inference, I’ve implemented a simple Python example demostrating how Bayesian Inference can be used for A/B-testing, that is, evidence based testing. This methodology, i.e. A/B-testing, is useful in most domains, e.g. … Continue reading

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Bayesian Inference for upcoming elections

In a couple of previous posts, I’ve tried to wear out my swedish speaking audience with predictions regarding the upcoming national elections, using Bayesian Inference. This post will be a bit more technical, perhaps of interest for a larger audience … Continue reading

Posted in Bayes, Big Data, Data Analytics, Data Driven Management, Math, Numpy, performance, Politik, Probability, Pystan, Python, Simulation, Society, STAN, Statistics, Sverige | Tagged , , , , , , , , , , | Leave a comment