Switzerland’s Gun Control Referendum - Constituency-Level Results from the EU Referendum - Statistics Assessment Answer

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Statistics Assessment Answer

TASK: QUESTION A: In Switzerland in 2011, a legally binding referendum was held that would have banned people from keeping guns at home, as well as introducing stricter background checks for those wishing to purchase them. The referendum failed, with 56% of voters opposing it. For this question, suppose that the referendum is going to be repeated next year, and the pro-gun-control campaign asks for your advice. Specifically, the campaign group wants to run an advertising campaign targeted at groups who are most likely to support the new referendum, to persuade them to turn out and vote. Your job is to tell them which types of people are most supportive of gun control. To help measure the likely effectiveness of their advertising, they also want to know how much each characteristic matters in explaining support. You’ll use a survey of voters taken after the first referendum that asked about support for gun control. You need to: i) Choose a logit model that predicts support for gun control, carefully justifying your selection of variables for the model. You must use a minimum of three independent variables. ii) Present the model’s findings in ways that clearly explain how much the variables matter in explaining support for gun control You should present your approach and your findings in the form of a brief report. It should conclude by explaining which types of people you think the campaign should target. The dataset is called “s” and is contained in the file “swiss. Rda”. It contains the following variables for each individual in the survey: QUESTION B: Estimating Constituency-Level Results from the EU Referendum In the 2016 UK referendum on leaving the EU, the results of the vote were not released for individual electoral constituencies. However, many scholars would like to know why people voted to leave the EU, and how support for leaving differed across constituencies. One previous study has already estimated constituency-level support for ‘leave’ in an authoritative way. Your tasks in this question are (i) to produce estimates of the percentage of voters that voted ‘leave’ in every constituency using multilevel modeling and post-stratification that are as close as possible to this existing set of estimates, as measured by the Mean Absolute Error (MAE), and (ii) to use your results to explain why people voted to leave. You need to: i) Estimate an appropriate logistic multilevel model explaining voting for leave, using the predictors in the dataset. ii) Present the multilevel model results and interpret how the variables affect voting to leave the EU (Note: you do not need to discuss statistical significance). iii) Produce post-stratified estimates of the percentage of people who voted ‘leave’ in all 631 constituencies in England, Scotland and Wales iv) Compare your results to the existing estimates using the Mean Absolute Error You should present and explain your approach and results in a brief report, explaining why your estimates do or not perform well compared to the existing estimates. Note: if you cannot get very close to the existing results, do not worry. Your grade depends on the quality of your analysis, presentation, and interpretation, not how close your results are to the existing estimates. The survey data is called “e” and is in the file “survey. Rda”. It comes from the 2017 British Election Study and it contains the following variables:

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