Fans of probability love random processes. And lotteries are a great example of random number generation. The UK National Lottery ran in one format from 19/11/1994 until 7/10/2015. I was talking to somebody who had played the same set of numbers in all of these lottery draws and I wondered what the net gain or […]
Tag: statistics
Lemonade Secret Drinker: sober statistics
I read this article on the BBC recently about alcohol consumption in the UK. In passing it mentions how many people in the UK are teetotal. I found the number reported – 21% – unbelievable so I checked out the source for the numbers. Sure enough, ~20% of the UK population are indeed teetotal (see […]
Parallel Lines: Spatial statistics of microtubules in 3D
Our recent paper on “the mesh” in kinetochore fibres (K-fibres) of the mitotic spindle was our first adventure in 3D electron microscopy. This post is about some of the new data analysis challenges that were thrown up by this study. I promised a more technical post about this paper and here it is, better late […]
My Blank Pages III: The Art of Data Science
I recently finished reading The Art of Data Science by Roger Peng & Elizabeth Matsui. Roger, together with Jeff Leek, writes the Simply Statistics blog and he works at JHU with Elizabeth. The aim of the book is to give a guide to data analysis. It is not meant as a comprehensive data analysis “how to”, […]
Where You Come From: blog visitor stats
It’s been a while since I did some navel-gazing about who reads this blog and where they come from. This week, quantixed is close to 25K views and there was a burst of people viewing an old post, which made me look again at the visitor statistics. Where do the readers of quantixed come from? Well, geographically they […]
The Great Curve: Citation distributions
This post follows on from a previous post on citation distributions and the wrongness of Impact Factor. Stephen Curry had previously made the call that journals should “show us the data” that underlie the much-maligned Journal Impact Factor (JIF). However, this call made me wonder what “showing us the data” would look like and how journals might […]
At a Crawl: Analysis of Cell Migration in IgorPro
In the lab we have been doing quite a bit of analysis of cell migration in 2D. Typically RPE1 cells migrating on fibronectin-coated glass. There are quite a few tools out there to track cell movements and to analyse their migration. Naturally, none of these did quite what we wanted and none fitted nicely into […]
My Blank Pages II: Statistics Done Wrong
I have just finished reading this excellent book, Statistics done wrong: a woefully complete guide by Alex Reinhart. I’d recommend it to anyone interested in quantitative biology and particularly to PhD students starting out in biomedical science. Statistics is a topic that many people find difficult to grasp. I think there are a couple of reasons for this […]
Tips from the blog IV – averaging
I put a recent code snippet put up on the IgorExchange. It’s a simple procedure for averaging a set of 1D waves and putting the results in a new wave. The difference between this code and Average Waves.ipf (which ships with Igor) is that this function takes the average of all points in the wave and […]
Wrong Number: A closer look at Impact Factors
This is a long post about Journal Impact Factors. Thanks to Stephen Curry for encouraging me to post this. tl;dr — I really liked this recent tweet from Stat Fact It’s a great illustration of why reporting means for skewed distributions is a bad idea. And this brings us quickly to Thomson-Reuters’ Journal Impact Factor […]