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Election - Hate Crime
Analysis
OMIS 694 – Applied Statistics for Business Analytics
Using SAS
Presented by:
Group I
Savya Keerthi Ravuri
Ramya Elizabeth Calius
Balakrishna Nandigam
Lalasa Reddy Gurram
Introduction
 What is hate crime ?
 Bias-motivated crimes
 What causes hate crime ?
 Motivational and Situational
What We Are Interested ?
 Factors tied to Donald Trump’s success in 2016 presidential elections.
 Impact of Donald Trump’s share of votes on hate crime rate post the elections.
Data Exploration
 36,000 hate crimes were reported between 2010-2015 by FBI.
 Average of 16 per day.
 900 hate crimes were reported in next 10 days after 2016 U.S presidential elections
by Southern Poverty Law Center.
 Average of 90 per day.
Challenges Faced
 FBI tracked data is from various agencies reported and SPLC collected is from
people’s self-reports.
 Identifying the data set at county level.
Hate crime statistics Nov 9th – 18th
0.0 0.5 1.0 1.5
hate_crimes_per_100k_splc
Wyoming
Washington
Utah
South Dakota
Pennsylvania
Ohio
New York
New Hampshire
Monta0
Minnesota
Maryland
Kentucky
India0
Hawaii
District of Columbia
Colorado
Arizo0
state
Hate crimesfor state after 2016 USpresidency elections
Variables
 Population Unemployed Rate
 Median Household Income
 Gini Index (Income Inequality)
 Share of white residents below Poverty
 Share of population not white
 Population from metro areas
 Population that are not U.S. citizens
 Share of adults 25 or higher with high
school diploma only
 Population from metro areas
 Average hate crimes from FBI between
2010-2015
 Rate of hate crimes for first 10 days after
2016 presidency elections.
Donald Trump’s election success analysis
 Test conducted – Multivariate Linear Regression
 Null Hypothesis – Socioeconomic variables doesn’t significantly determine Donald
Trump’s success in 2016 US presidential elections.
 Alternative Hypothesis – Socioeconomic variables significantly determine Donald
Trump’s success in 2016 US presidential elections.
Analysis
 How different factors
impact share of voters
voted for Donald Trump
in 2016 U.S Presidency
elections ?
Regression Equation
Shareofvoters = b0 + b1 *unemploymentrate + b2 *Median_Houesehold_income+
b3*Gini_index + b4*share_non_white + b5*percent_of_adults_with_a_high_sc
Pre-election hate crime analysis
 Test conducted – Multivariate Linear Regression
 Null Hypothesis – Socioeconomic variables doesn’t determine hate crimes rate
observed in 2010-2015 period.
 Alternative Hypothesis – There is at least one socioeconomic variable that
determine hate crimes rate observed in 2010-2015 period.
Analysis
 Does the median household
income or unemployment rate
effects the hate crime rate?
Analysis
 How does non-white
population effects the hate
crime in USA?
Analysis
 which socioeconomic factor
majorly effects the hate crime
rate?
Regression equation:
Avg_Hatecrime_ = b0 + b1* gini_index + b2*share_non_white +
Per_100K_FBI b3* share_population_with_high_school
Post-election hate crime analysis
 Test conducted – Multivariate Linear Regression
 Null Hypothesis – Socioeconomic variables doesn’t determine high raise in the hate
crime rate within 10 days after elections.
 Alternative Hypothesis – There is at least one socioeconomic variable that
determine high raise in the hate crime rate within 10 days after elections.
Analysis
 Does the number of
population voted trump is a
significant determinant for
population-adjusted hate
incidents across the country?
Regression equation:
Hatecrime_Per_ = b0 + b1* gini_index + b2*share_non_white +
100K_SPLC b3* share_voters_voted_trump
Analysis
 As the same factors were linked to hate
incidents for both analysis, it is still uncertain
that hate incidents truly increased after the
election due to the trump victory.
Post-election hate crime analysis
Pre-election hate crime analysis
To
Summarize
Analysis conducted on Donald Trump’s
election win.
Analysis on rate of hate crime during
pre-election and post election period.
How far Donald Trump’s share of votes
affected the rise in crime rate.
Questions ?
Thank You

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Election hate crime analysis

  • 1. Election - Hate Crime Analysis OMIS 694 – Applied Statistics for Business Analytics Using SAS Presented by: Group I Savya Keerthi Ravuri Ramya Elizabeth Calius Balakrishna Nandigam Lalasa Reddy Gurram
  • 2. Introduction  What is hate crime ?  Bias-motivated crimes  What causes hate crime ?  Motivational and Situational What We Are Interested ?  Factors tied to Donald Trump’s success in 2016 presidential elections.  Impact of Donald Trump’s share of votes on hate crime rate post the elections.
  • 3. Data Exploration  36,000 hate crimes were reported between 2010-2015 by FBI.  Average of 16 per day.  900 hate crimes were reported in next 10 days after 2016 U.S presidential elections by Southern Poverty Law Center.  Average of 90 per day. Challenges Faced  FBI tracked data is from various agencies reported and SPLC collected is from people’s self-reports.  Identifying the data set at county level.
  • 4. Hate crime statistics Nov 9th – 18th 0.0 0.5 1.0 1.5 hate_crimes_per_100k_splc Wyoming Washington Utah South Dakota Pennsylvania Ohio New York New Hampshire Monta0 Minnesota Maryland Kentucky India0 Hawaii District of Columbia Colorado Arizo0 state Hate crimesfor state after 2016 USpresidency elections
  • 5. Variables  Population Unemployed Rate  Median Household Income  Gini Index (Income Inequality)  Share of white residents below Poverty  Share of population not white  Population from metro areas  Population that are not U.S. citizens  Share of adults 25 or higher with high school diploma only  Population from metro areas  Average hate crimes from FBI between 2010-2015  Rate of hate crimes for first 10 days after 2016 presidency elections.
  • 6. Donald Trump’s election success analysis  Test conducted – Multivariate Linear Regression  Null Hypothesis – Socioeconomic variables doesn’t significantly determine Donald Trump’s success in 2016 US presidential elections.  Alternative Hypothesis – Socioeconomic variables significantly determine Donald Trump’s success in 2016 US presidential elections.
  • 7. Analysis  How different factors impact share of voters voted for Donald Trump in 2016 U.S Presidency elections ? Regression Equation Shareofvoters = b0 + b1 *unemploymentrate + b2 *Median_Houesehold_income+ b3*Gini_index + b4*share_non_white + b5*percent_of_adults_with_a_high_sc
  • 8. Pre-election hate crime analysis  Test conducted – Multivariate Linear Regression  Null Hypothesis – Socioeconomic variables doesn’t determine hate crimes rate observed in 2010-2015 period.  Alternative Hypothesis – There is at least one socioeconomic variable that determine hate crimes rate observed in 2010-2015 period.
  • 9. Analysis  Does the median household income or unemployment rate effects the hate crime rate?
  • 10. Analysis  How does non-white population effects the hate crime in USA?
  • 11. Analysis  which socioeconomic factor majorly effects the hate crime rate? Regression equation: Avg_Hatecrime_ = b0 + b1* gini_index + b2*share_non_white + Per_100K_FBI b3* share_population_with_high_school
  • 12. Post-election hate crime analysis  Test conducted – Multivariate Linear Regression  Null Hypothesis – Socioeconomic variables doesn’t determine high raise in the hate crime rate within 10 days after elections.  Alternative Hypothesis – There is at least one socioeconomic variable that determine high raise in the hate crime rate within 10 days after elections.
  • 13. Analysis  Does the number of population voted trump is a significant determinant for population-adjusted hate incidents across the country? Regression equation: Hatecrime_Per_ = b0 + b1* gini_index + b2*share_non_white + 100K_SPLC b3* share_voters_voted_trump
  • 14. Analysis  As the same factors were linked to hate incidents for both analysis, it is still uncertain that hate incidents truly increased after the election due to the trump victory. Post-election hate crime analysis Pre-election hate crime analysis
  • 15. To Summarize Analysis conducted on Donald Trump’s election win. Analysis on rate of hate crime during pre-election and post election period. How far Donald Trump’s share of votes affected the rise in crime rate.