An automated review of thinkingdan indicates that people are reading this blog, despite the fact that I am woefully negligent of it. Perhaps I should write more about vegetarianism and morality, since that is the main thing that people stumble on the blog for…?
I’m very amused by the positive spin on the numbers below. I like the imagery of forcing 7 planeloads of people to read my blog on transatlantic flights, perhaps handed out on the back of the safety card.
Comments welcome! The automated part follows….
The stats helper monkeys at WordPress.com mulled over how this blog did in 2010, and here’s a high level summary of its overall blog health:
The Blog-Health-o-Meter™ reads This blog is doing awesome!.
A Boeing 747-400 passenger jet can hold 416 passengers. This blog was viewed about 2,600 times in 2010. That’s about 6 full 747s.
In 2010, there were 14 new posts, growing the total archive of this blog to 47 posts. There were 26 pictures uploaded, taking up a total of 7mb. That’s about 2 pictures per month.
The busiest day of the year was August 21st with 38 views. The most popular post that day was Vegetarianism Argument Map.
Where did they come from?
The top referring sites in 2010 were anthropology.net, danandannalawson.pwp.blueyonder.co.uk, digg.com, facebook.com, and maths.bris.ac.uk.
Some visitors came searching, mostly for i think therefore i am, vegetarianism, do races exist, morality of vegetarianism, and thinking cartoon.
Attractions in 2010
These are the posts and pages that got the most views in 2010.
Vegetarianism Argument Map April 2010
Breaking news: do human races exist after all? January 2010
The logical morality of vegetarianism August 2008
I think therefore I am…. July 2008
Vegetarianism around the world July 2008
There has been less evidence of thinking of late. As in, I’ve not posted anything since we moved to Bristol in October! Does that mean I’ve not been thinking? Or does it mean I’ve been thinking about more useful things? I suspect a little of both…
Well, I’m back now and I hope to post about a good number of interesting things! I have been thinking about work rather more down here since its really rather interesting. I’m studying bacteria – in particular, how we can understand their evolution. I want to spend a little time explaining this for non-experts, sometime over the Christmas period. Stay tuned! Or don’t… 😉
I can summarise my thoughts for the past three months quite easily – I’m happy! Work is going well, I have a paper accepted after a long period of waiting, we have many friends in Bristol and its all jolly good fun. I hope this excuses the lack of posts and promise to begin rectifying this in the new year. I am resolute.
Resolutions… there is a topic for a blog post!
I’ve been quiet recently – its the danger of computer games! Oops…
It really does feel like an addiction sometimes. I don’t play games very often, but when I do… well, I’m gone until I’ve had my Fix. This was System Shock 2 – a very old game now, but still great. There is nothing as scary as creeping around the dark corridors of an abandoned station, hearing the moans and clunks of the monsters hunting you, knowing you’ve only got one bullet left and they can kill you in one swipe.
Well, perhaps there is. I got some VERY scary looks from Anna for playing so long! Heh…
But now I’m back, the itch is scratched and I can continue with life again. Until Spore comes out of course!
Whilst Beer hardly counts as thinking, thinking about beer does, and since I’m writing about it here, I’m thinking about thinking about beer. For others who do, I’m contributing to Andy’s Beer Blog. Check it out.
Or maybe you are just too stupid. These people would like to sell you a throw featuring the bacterial flagellum, which are a pretty darned complex piece of kit that allow bacteria to move around. But as explained here there is a perfectly sensible explanation for them, from origin to as we see them now.
Why are people arrogant enough to assume that because they don’t understand something, it is beyond understanding? After over 6000 years of history, we still make the same mistakes. Of course, thinking we understand something is an equally dangerous error: we should be always open to the possibility that we are wrong. All people, including scientists, make both types of mistake – but science as a system is open to change, and Religion is not. This is why religion should never have anything to do with science, and why it will keep being forced back into the realm of the unexplained. Its up to the individual to decide if God has a place for themselves – they should not use God to try to explain the world, nor science to disprove God.
It seems that I have started blogging about science at the wrong time – there will soon be nothing to talk about. This is according to Wired: The End of Theory: The Data Deluge Makes the Scientific Method Obsolete. Roughly speaking, we are not going to need scientific theory anymore, because the data are much better a description without it. (Incidentally, google has all the data.)
Of course, such a revelation has made waves in the press and of course the blogosphere. As a theoretician I feel somewhat defensive about having a job, so I’m going to join the crowds by explaining why this just very very wrong. Its quite simple really. The Scientific method works as follows:
- Observe a phenomenon (i.e. data).
- Form a hypothesis about the cause (i.e. explain the data).
- Think of a new way to test the hypothesis (i.e. get more data).
- Perform the test. If it fails, go to 2. If it succeeds, go to 3.
- Use the hypothesis as a prediction.
The scientist keeps gathering data and the hypothesis gains evidence and becomes accepted over time – unless of course some new piece of evidence is found that cannot support the hypothesis. Hence science is formed as a set of theories that can change with the evidence. The hypothesis can be used to make predictions, and provides an explanation for the phenomenon.
The new concept notes that we have more evidence than we know what to do with right from the beginning. In fact, by statistically describing the data, we can skip straight from 1 to 5: the data is the model. Predictions can be made without ever having to think about what the data means.
This sounds great, until one thinks a little about the nature of prediction. There are two main types of prediction: interpolation and extrapolation. Interpolation means considering what happens in between two regions that we have measurements for, and statistical models are perfect for this. Extrapolation means considering things outside the measured data. Statistical techniques are really bad for this, because two descriptions can be just as good for the data itself, whereas they give wildly different predictions outside of it. The only solution is to know what on earth is going on and to predict based on that. The only way to achieve this is to build a model for its behaviour, based upon repeated testing of what it does.
To give an example: in my own research I consider the behaviour of bacteria in the human gut. You can’t measure it. People eat food, and stuff comes out the other end. That’s all you get. But: you can model the gut by building an experiment with similar properties. And you can model the experiment with maths, and use that to predict what is happening in our gut. You can’t do this any other way because the data don’t tell you anything about what is going on inside the gut itself. You can mathematically PROVE that there is not enough information in a googleplex of measurements on a live person. You need the experiment, and to include the differences between the experiment and the body, you need the model.
Google data may be coming out of our arses, but we’ve no idea where its been in between.
This is a blog by Daniel Lawson about Science, life, geekiness and anything else that occupies my mind whilst within range of a computer. Welcome! I hope it develops into something interesting enough to bring you here.