An introduction to their relationship through the gravity model
In my previous article I introduced the basic concepts of probability and how this relates to maximum likelihood estimation and ordinary least squares regression. In this article, I will continue to build on this foundation but in the case of Poisson regression through its application to the gravity model.
In contrast to linear regression, which assumes that the dependent variable is normally distributed with constant variance, Poisson regression assumes that the target variable distribution has a Poisson distribution. Thus, the variance of the independent variable is expected to equal to its mean. This is used in the case where we…
An introduction to their relationship and their workings
In my research I have come across the idea of maximum likelihood estimation quite a few times. However, without the statistical background of those that traditionally work in my field I often found it difficult to understand or follow some of the models they create and develop. A big part of this was their use of maximum likelihood estimation methods an their link to regression frameworks. …
The application of ‘The Checklist Manifesto’ to data Science
Atul Gawande is an American surgeon, notable for his four best-selling books of ‘Complications’, ‘Better’, ‘Being Mortal: Medicine and What Matters in the End’ and ‘The Checklist Manifesto, a MacArthur Fellowship grant, and many other accolades that if you want to know more you can read his bio from the New Yorker.
While he is indeed a surgeon, and three of his bestselling books are about medicine, in 2009 he wrote his book ‘The Checklist Manifesto’ in which he describes the usefulness of checklists and why are beneficial in a variety of complicated and complex situations. The examples he provides…
Why Geography still matters when everything is online
With lockdowns and restrictions occurring all over the world due to Covid-19 we have seen an acceleration in the trend towards online, whether that is online meet ups, at home working online, or online shopping. While it may feel like these trends are resulting in shifts away from physical formats, such as office spaces, stores and cafes, the shift towards online still is still affected by geography in a variety of ways. This is especially so in the case of ecommerce, notably in the grocery sector whereby access is still heavily mediated by the physical infrastructure in place.
Firstly, geography…
Why you should definitely get involved in one if you can!
This weekend I took part in my first ever hackathon, Hex Cambridge. I have been wanting to take part in one for a long time now, but whenever one came up that I was interested in I always found an excuse not to take part, admittedly mostly because I was scared I wasn’t going to be good enough or I wasn’t going to enjoy it. It's fair to say that I should have gotten involved much sooner and I would definitely advise anyone who is thinking of doing one to go ahead!
So what is a hackathon? In short, it…
Are we seeing a truly ‘positioneless’ league emerge?
Admittedly I am a huge fan of the NBA even though I am based in the UK so I don’t get to see much of the games. This means that I get my fix mostly from following the stats and the highlights after the games. Although I regret that I don’t get to watch as many games as I like, the analytical side of me enjoys being able to watch and follow the stats, usually being able to roll them off my tongue to any unsuspecting victim that engages me on the topic. Given this though, I thought it would…
Similarities to a long term data science project
As we move towards the holiday break and a well-deserved rest for all, I am drawing to an end of my first term as a PhD student, and my first full online term at that. At this point, I thought it would be good to reflect on what has gone on, how I’ve felt, what I have achieved and what comes next going forward so that I am aware of where I currently am and where I want to be going forward.
In this sense, one of the main things I have learnt is that, even though this is a…
geographic data science mapping in python
To give a bit of context, I am currently working on a paper that is looking at what distance do patent citations start to decline. This is so that we can try to measure how far knowledge may actually travel and whether there are any restrictions to this, such as language, technology or institutional barriers. This was part of my Master’s dissertation and I am currently working with my supervisor to get it into a format that may potentially be published (or at least that is the hope). One of the things to try to improve its overall look and…
Applying a decision tree classifier to the iris dataset
There are plenty of articles out there that explain what a decision tree is and what it does:
So here I am going to focus on how a decision tree may be implemented using the scikit-learn library in python on the iris dataset, along with some of the functionality that is useful in analysing the performance of the algorithm.
What is a classifier?
A classifier algorithm is used to map input data to a target variable through decision rules and can be used to predict and understand what characteristics are associated with a specific class or target. This means that…
1 down, 35 more to go…
While many of the same feelings of anxiety, fear and excitement remain from my first week as a PhD student (see the article here), I am starting to get my head around the beast that is a three year PhD. Of course, I say that it is a beast because of all the things that have to be done in the course of three years, which when writing this, three years seems like both a long and a short time. A long time in that it is as long as I spent doing my undergraduate, longer than I spent at…
Philip Wilkinson
A PhD student at the Centre for Advanced Spatial Analysis, UCL, looking to develop his coding skills! www.linkedin.com/in/philip-wilkinson-02917b150
