POL252: Political Research - Brexit Results - Report Writing Assignment Help

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Political Research Assignment Help

Task: Dataset BrexitResults.RData The following list of variables is your codebook: Project Motivation You are a civil servant working in the Cabinet Office in the aftermath of the EU Referendum. As expected, the government is dismayed with the result and they need a quick answer of what happened and why. After several conversations, ministers need to get some insight on three different theories that have been going around:

1. This is an anti-London reaction, which is reflected by a large difference in the votes for the referendum in London, compared to the rest of the country.
2. This is the result of rising immigration. People living in areas with a higher proportion of immigrants voted for Brexit as a way to regain control on immigration.
3. This is the work of UKIP. Their surprising results in 2015 were simply a warning of what was about to come. UKIP vote is a good predictor of the referendum outcome.

Specific tasks In order to answer the questions posited by the ministers, you should first examine the relevant variables individually (e.g. BrexitVote, London, BornUK and UKIP15). For that, please provide the following: A Table with all the variables, the relevant measure of central tendency (MCT), and the relevant measure of dispersion (MD). The table should look like this: The relevant plot for every variable. Then, you should perform some recodes of the variables of interest, in particular, BornUK and UKIP15. For each variable, create a corresponding binary variable where 0 corresponds to a value that is equal or below the median, and 1 corresponds to a value above the median. You should make sure you name the new variables in an intuitive way (e.g. BornUK_binary) Once you do that, you should examine the relationship between the brexit vote share and the relevant variables, For that, you will need to produce - for each theory - the following:

• A justification for the proposed relationship.
• A conditional distribution plot
• A two-sample t-test.

Finally, you should discuss your results. Do you find support for some of the propositions mentioned above? Which one seems to be more relevant?

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