# Posts Tagged ‘ statistics ’

## Mathematics teaching Rockstar – Jo Boaler

July 25, 2016
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Moving around the education sector My life in education has included being a High School maths teacher, then teaching at university for 20 years. I then made resources and gave professional development workshops for secondary school teachers. It was exciting … Continue reading →

## On accuracy

July 22, 2016
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In our last article on the algebra of classifier measures we encouraged readers to work through Nina Zumel’s original “Statistics to English Translation” series. This series has become slightly harder to find as we have use the original category designation “statistics to English translation” for additional work. To make things easier here are links to … Continue reading On accuracy

## A budget of classifier evaluation measures

July 22, 2016
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Beginning analysts and data scientists often ask: “how does one remember and master the seemingly endless number of classifier metrics?” My concrete advice is: Read Nina Zumel’s excellent series on scoring classifiers. Keep notes. Settle on one or two metrics as you move project to project. We prefer “AUC” early in a project (when you … Continue reading A budget of classifier evaluation measures

## What if the RNC assigned seating randomly

July 21, 2016
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The punditry has spoken: the most important data question at the Republican Convention is where different states are located. Here is the FiveThirtyEight take on the matter: They crunched some numbers and argue that Trump's margin of victory in the...

## Bayesian Bootstrap: The Movie + Some Highlights from UseR! 2016

July 20, 2016
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Not surprisingly, this year’s UseR! conference was a great event with heaps of talented researchers and R-developers showing off the latest and greatest R packages. (A surprise visit from Donald Knuth didn’t hurt either.) What was extra great thi...

## Coupling of particle filters: smoothing

July 20, 2016
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Hi again! In this post, I’ll explain the new smoother introduced in our paper Coupling of Particle Filters with Fredrik Lindsten and Thomas B. Schön from Uppsala University. Smoothing refers to the task of estimating a latent process of length , given noisy measurements of it, ; the smoothing distribution refers to . The setting is state-space […]

## Coupling of particle filters: likelihood curves

July 19, 2016
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$Coupling of particle filters: likelihood curves$

Hi! In this post, I’ll write about coupling particle filters, as proposed in our recent paper with Fredrik Lindsten and Thomas B. Schön from Uppsala University, available on arXiv; and also in this paper by colleagues at NUS. The paper is about a methodology with multiple direct consequences. In this first post, I’ll focus on correlated likelihood estimators; in a later […]

## What happened when I was forced to wait 30 minutes for the subway

July 18, 2016
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What happened when I was forced to wait 30 minutes for the subway: pondering how easy it is for data analysts to get fooled by bad data

## Mittag-Leffler function and probability distribution

July 17, 2016
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The Mittag-Leffler function is a generalization of the exponential function. Since k!= Γ(k + 1), we can write the exponential function’s power series as and we can generalize this to the Mittag=Leffler function which reduces to the exponential function when α = β = 1. There are a few other values of α and β for […]

## the curious incident of the inverse of the mean

July 14, 2016
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A s I figured out while working with astronomer colleagues last week, a strange if understandable difficulty proceeds from the simplest and most studied statistical model, namely the Normal model x~N(θ,1) Indeed, if one reparametrises this model as x~N(υ⁻¹,1) with υ>0, a single observation x brings very little information about υ! (This is not a […]