Showing posts with label causation. Show all posts
Showing posts with label causation. Show all posts

Saturday, 13 August 2011

Riots in England: Conflating Correlation with Causation

It is an elementary point in statistics that it is not wise to infer causation from correlation. While it might appear that two variables have a causal relationship, it is possible that they do not. An example commonly used to illustrate this point is:

As ice cream sales increase, so does the rate of deaths from drowning.
Therefore ice cream causes drowning.


This reasoning ignores the mediating variable, i.e. good weather, which actually explains both the increase in ice cream sales and the increase in rate of deaths from drowning. This is a simple example that is used to make a point.

After the recent riots in London and other English cities, most on the left are attributing the events to "deprivation". Some have mapped the location of the riots on top of deprivation data (only including London, for some reason), observed a pattern, and decided that it's case closed. Not so fast! What pattern would be observed if we were to look at the relationship between other variables and rioting areas? I'm going to use population density and proportion of area that is non-white here, because they are variables that the left will not want to consider.


































Table 1 depicts the 40 highest ranking Local Authorities for each of the following measures, separately: average LSOA score on Indices of Deprivation 2010, population density, and proportion of population that is non-white. The Local Authorities in bold font are those for which I was able to find evidence of rioting having taken place. The table quite clearly indicates that if someone wanted to pick a variable and claim it as an explanation, they'd chose population density or proportion of population that is non-white, and not deprivation. Not only do more of the LAs where rioting took place rank highly on these variables, they seemingly account for those areas which were considered surprising from the deprivation perspective. For example, while Croydon and Ealing are right up there on these measures, they're not high on the deprivation index (107 and 80, respectively).

Of course, the left wouldn't even entertain the idea that these variables might have some explanatory value. They dismiss them out-of-hand, as they're not interested in anything which would lead to arguments against over-population or immigration. They are ideologically obsessed with equality, and they will always perceive events in this context. That they're so impressed by misleading maps simply plotting one variable against another demonstrates that they're not at all practiced in arguing from evidence. Take this entry on the Greek Left Review blog as an example.

In summary, the purpose of this post is to highlight that inferring causation from correlation is not a sensible practice and that variables other than deprivation can be used in a similarly simplistic fashion to 'prove' entirely different arguments.