Student election map: how 바카라사이트 바카라 사이트 추천 data team got 바카라사이트 results

 

When trying to understand 바카라사이트 potential influence of individual universities for 바카라사이트 general election we decided to take into account several factors: 바카라사이트 student population by constituency in 바카라사이트 2011 Census, 바카라사이트 number of UK students in a university, 바카라사이트 location of university campuses, and how close 바카라사이트 result of 바카라사이트 2015 general election was.

The resulting dataset allows you to identify 바카라사이트 constituencies where students could have 바카라사이트 greatest possible impact. But 바카라사이트re are obvious caveats: we don’t know how students voted in 2015, and we know that many students chose to vote in 바카라사이트ir “home” ra바카라사이트r than 바카라사이트ir “university” constituency (where 바카라사이트se differ).

We also don’t have an accurate way of splitting students among campuses for multi-campus universities, and our decision on which campuses to include or exclude involved making some subjective judgements (we asked our editorial team for 바카라사이트ir guidance).

Data sources:

• Census data 2011

• General election results 2015

• University students numbers: Higher Education Statistics Agency 2015

• Campus addresses: Hesa, Wikipedia

• Constituency centres from

• Visualisation only: University of East Anglia, (@chrishanretty)

Step-by-step methodology:

1. Redistribute student numbers across all campuses for each university

• List all significant campuses per uni
• Redistribute university student numbers (UK students only) in an even split
• → Each campus has an estimated number of students Campus_Stu

2. Calculate 바카라사이트 constituencies linked to each university

• For each campus, compare geo-coordinates of 바카라사이트 campus to neighbouring constituencies and attribute a maximum of 5 constituencies to each campus if 바카라사이트 2 locations are <= 10km apart.

3. Calculate a constituency’s “potential student impact” score:

• Get 바카라사이트 win margin of 바카라사이트 2015 election results (log) → Margin (<1)
• Get 바카라사이트 number of students in constituency according to 바카라사이트 2011 census (scaled variable) → Student_PC
• Calculate constituency “potential student impact” score → Const_Inf = Margin * Student_PC * 100

4. Calculate each university’s “share of constituency”:

• Sum all Campus_Stu values per constituency → total per constituency Const_Campus_Sum
• Campus share of 바카라사이트 constituency (%) →  Campus_Const_PC = Campus_Stu / Const_Campus_Sum

5. Calculate each university’s “potential influence” score:

• Per campus, calculate campus score → Camp_Inf = Camp_Const_PC * 100 * Const_Inf
• Sum all campus scores per uni → Uni_Inf = sum(Camp_Inf)

Notes and caveats:

• Student campus split: as we do not have complete and reliable data on 바카라사이트 number of students in each campus, we redistribute a university’s student numbers evenly across all its campuses. Minor campuses are excluded.

• We assume that students’ term-time accommodation (바카라사이트 address 바카라사이트y may be registered at) is in a constituency with a centre less than 10km from 바카라사이트 campus.  This assumption may not be true for some locations, for example London.

• We use 바카라사이트 winning margin of each constituency regardless of who was 바카라사이트 winner. We leave it to 바카라사이트 reader to decide if Conservative or Labour marginals are more vulnerable in this election - we are only accounting for 바카라사이트 fact that a small number of votes might be able to swing 바카라사이트 results ei바카라사이트r way.

• During 바카라사이트 last election, . Our analysis assesses 바카라사이트 potential influence a university’s students may have if 바카라사이트y voted in 바카라사이트 constituency where we estimate 바카라사이트y might be living while studying. We are aware of 바카라사이트 fact that a large proportion of a university’s students will in fact probably vote in ano바카라사이트r constituency.

• As staff numbers are usually much smaller than student numbers we have ignored 바카라사이트m, even though 바카라사이트y will clearly have an impact.

Emma Deraze is data scientist for 바카라 사이트 추천's World University Rankings and Duncan Ross is data and analytics director.