Where are the Brexiteers?

Every year, the Hansard Society sponsors a survey on political engagement in the UK.

They put topical questions in each survey. For the 2016 / 7 survey, they asked about how people voted in the Brexit referendum.

Luckily, they make the data freely available online for us to analyze.

You can get the data for yourself from the UK Data Service: https://discover.ukdataservice.ac.uk/catalogue/?sn=8183. There are data files in various formats, including:

  • SPSS format (for the SPSS statistical package);
  • Stata format (for the Stata statistical package);
  • tab-delimited (a general data format, that can be used with Excel and other packages).

The data is in a standard form, with one row per respondent, and one column per question.

To save you a tiny bit of work, I’ve made an unchanged copy of the tab-delimited version of the data file for you to download directly. I’ve also made a copy of the document describing the questions they ask and the way that they have recorded the answers in the data file. This is often called the “data dictionary”. It was originally in Rich Text Format, but I have converted to PDF for convenience. It is otherwise identical to the file you will find at the UK Data Service.

You can download these copies of the files from the following links:

In the moment, we are going to try and analyze these data. We will focus on two questions labeled cut15 and numage. cut15 is the question about Brexit. The data dictionary has the variable label “CUT15 - How did you vote on the question ‘Should the United Kingdom remain a member of the European Union or leave the European Union’?”. The recorded values run from 1 through 6 and have the following labels:

Value label information for cut15
Value = 1.0    Label = Remain a member of the European Union
Value = 2.0    Label = Leave the European Union
Value = 3.0    Label = Did not vote
Value = 4.0    Label = Too young
Value = 5.0    Label = Can't remember
Value = 6.0    Label = Refused

We also want the variable numage; this is the age of the respondent in years.

Your task is the following:

  • Load the data.
  • Check the values for cut15 and numage. Are there any bad values? If there are, remove the respondents (rows) that have invalid values in either variable.
  • In this clean dataset, find the number of people who admitted to voting Remain. Find the number of people who admitted to voting Leave. Calculate the ratio of Leave voters to (voters who voted either Leave or Remain).
  • Write down every step of what you did, so that someone else can reproduce it.

Remember, the final referendum vote percentages were:

  • Remain: 48.1%
  • Leave: 51.9%

Did the proportion you find, match the proportion in the referendum? How far off was it? Is it too far off? Think about what “too far” could mean.