Demographic and Socio-Economic Profiles that Relate to Poli

Demographic and Socio-Economic Profiles that Relate to Political Party Affiliation

Examined in Massachusetts and Wyoming for the 2016 Presidential Election

Group 4:Mason ChengEryn HallAlex RhodeBailey Boulter

Outline

ObjectiveHypothesisStudy CharacteristicsMethodologyResultsAnalysisConclusionDegree of Accuracy

Background

The 2016 Presidential election consist of 4 main competitors 2 Main Democratic candidates: Hillary Clinton & Bernie Sanders 2 Main Republican candidates: Donald Trump & Ted Cruz Series of primaries and caucuses take place between February 1st and June 14 2016. Massachusetts had their primaries on March 1st Winners: Donald Trump & Hillary ClintonWyoming had their caucus on April 9th Winners: Bernie Sanders and Ted Cruz

Objectives

To

discover if there is a

relationship or correlation

between election

outcomes (party affiliation)

and

demographic and socio-economical variables

Looking at two extreme states (one red, one blue)

Variables: population density, civilian labor force, veterans, education, ethnicity/race, sex, foreign-born, health insurance, disability, age, per-capita income, and poverty

To see if social stereotypes of political party affiliation attributes hold true

To develop experience of gathering data from reputable sources, and then modifying it for geo-spatial analysis

s

, etc.

Hypothesis

There will be a correlation between the 2016 presidential election results and the selected demographic and socio-economic factors

There will also be a significant difference in measured indicator variables between the two extreme states

Study Characteristics

Choice of States: Massachusetts and Wyoming

W

anted two extreme states (one red, one blue)

Wyoming was uniformly red and Massachusetts was uniformly blue

Geographically different regions different

people

Choice of Indicators

Wanted to test accuracy of social stereotypes of political parties

Focused on both social

and

economical variables that were presented by the most recent census(2010)

Methodology

Choose 10-12 indicators that may relateto political party affiliationSort and compile data from US CensusConvert Excel spreadsheets into DBF files On ArcMap, join the DBF tables based on a unique county valuesExport joined table as a shapefile Manipulated visual components of each individual shapefile to help compare two the two states

Population Density:Wyoming Alone

Results

Population Density (cont.)

Age Distribution

Female (percent)

Race/Ethnicity

Hispanics

Race/Ethnicity

Blacks

Race/Ethnicity

Whites

Education (Bachelor’s Degree)

Labor Force

Per Capita Income

Poverty

Disabilities

Health Coverage

Veterans

Foreign Born

Analysis

Much of our results were as expected based off of what we knew about voting trends.

Ex.

Education, Age Distribution, Non-Hispanic Whites, Foreign Born

However, there were some surprises

Health insurance coverage was high in areas with high poverty—Medicaid?

Relatively high Hispanic populations in

Wyoming

Not all of our indicators gave us the expected trends, or even any decipherable trends at all

Correlation does not equal causation

Conclusion

Overall, this study was designed to explore trends in voting and attempt to predict certain outcomes based on these trends.

Some

trends in voting were substantiated by our demographic data, others were inconclusive, and other interesting patterns were revealed in the plotting of this

data.

E.g. Poverty, Gender, Foreign Born voters

Conclusion

HOW MIGHT CANDIDATES & CAMPAIGN MANAGERS USE THIS INFORMATION?

Realistically, in states as “red” and “blue” as Wyoming and Massachusetts,

it’s

unlikely they would be won by the opposing party.

However, during primary season, candidates only run against other

members of

their party.

By knowing what demographic groups prevail in certain counties, candidates can strategize their campaigning efforts within a state to areas they are confident they may have a better chance of gaining support in.

Donald Trump and adults without bachelor’ degrees

Hillary Clinton and adults ages 65 and

over

Degree of accuracy

Other unmeasureable indicatorsi.e. Parental influence, religion, gun control, etc.Possibilities of Error due to:Low population density in WyomingLow voter turnout in Wyoming (about 3% of the total population)Difference in two states (size, etc.) making scales/legends different and difficult to createOlder census data (mostly from 2010) Low number of indicators used No real statistical math was used to determine if an indicator was statistically significant Correlation not causation