1. What it Takes to Make History Torbjorn Bjering Ho-Jung Hsiao Eric Griffin Chun-Hung Lin Gulsah Gunenc Gaoyuan Tian Laura Braeutigam Torbjorn Bjering Ho-Jung Hsiao Eric Griffin Chun-Hung Lin Gulsah Gunenc Gaoyuan Tian Laura Braeutigam

2. Table of Contents  Introduction  Brief Summary  Descriptive Statistics  Exploratory Data Analysis  Statistical Analysis  Conclusions  Introduction  Brief Summary  Descriptive Statistics  Exploratory Data Analysis  Statistical Analysis  Conclusions

3. Introduction  A lot goes into winning an election.  There are many factors that can lead a candidate to victory.  A campaign is based on what is important to the population.  A candidate’s image will help him appeal to many different aspects of society.  A lot goes into winning an election.  There are many factors that can lead a candidate to victory.  A campaign is based on what is important to the population.  A candidate’s image will help him appeal to many different aspects of society.

4. What are we studying?  The 2008 Presidential election  Obama vs. McCain  How do different aspects of society influence the result of the election?  Why do they affect the outcome?  The 2008 Presidential election  Obama vs. McCain  How do different aspects of society influence the result of the election?  Why do they affect the outcome?

5. Why are we studying the election?  Monumental event in our nation’s history  Something that affects all Americans  Abundant accurate data  Recently occurred  Monumental event in our nation’s history  Something that affects all Americans  Abundant accurate data  Recently occurred

6. How are we studying the election?  Extracting data from U.S. Census Bureau  50 states plus District of Columbia  DC is an outlier!  Evaluating exploratory data  LSM Regression  Gender  Age  Financial Status  Education  Religion  Race  Extracting data from U.S. Census Bureau  50 states plus District of Columbia  DC is an outlier!  Evaluating exploratory data  LSM Regression  Gender  Age  Financial Status  Education  Religion  Race

7. Brief Summary  Obama won the election.  Who support Obama?  Women  Younger voters  Voters with higher income  Highly educated voters  Jewish voters  Minority groups  Obama won the election.  Who support Obama?  Women  Younger voters  Voters with higher income  Highly educated voters  Jewish voters  Minority groups

8. Exploratory Data Analysis  An approach to analyze data for the purpose of formulating hypotheses worth testing, complementing the tools of conventional statistics for testing hypotheses.  Analyzing scatter diagrams to see if we can use linear regression  An approach to analyze data for the purpose of formulating hypotheses worth testing, complementing the tools of conventional statistics for testing hypotheses.  Analyzing scatter diagrams to see if we can use linear regression

9. Descriptive Statistics  Dependent Variable  Obama election percentage  Independent Variable  Minority Population  Black  Native American  Hispanic  Asian  Dependent Variable  Obama election percentage  Independent Variable  Minority Population  Black  Native American  Hispanic  Asian

10.  Independent Variable  Gender  Age  Religion  Christian  Jewish  Education  Persons with Bachelor's Degree or More  Financial Status  Unemployment Rate  Personal Income Per Capita in Current Dollars  Energy Consumption Per Capita  Homeownership Rate  Independent Variable  Gender  Age  Religion  Christian  Jewish  Education  Persons with Bachelor's Degree or More  Financial Status  Unemployment Rate  Personal Income Per Capita in Current Dollars  Energy Consumption Per Capita  Homeownership Rate Descriptive Statistics cont.

11. Statistical Analysis  Analyzing collected data for the purposes of summarizing information to make it more usable and/or making generalizations about a population.

12. Obama vs. Minority  Effect of minority groups are positive.  Asian is more supportive to Obama than other groups.  All coefficients except Hispanic and Native are significant. Minority = 100-white

13. Obama vs. Minority Blacks DC Minority (%)Blacks (%) Minority DC

14. Obama vs. Gender  Women are more supportive to Obama than men.

15. Obama vs. Gender DC (Male %) (Female %) MaleFemale

16. Obama vs. Age  All groups of ages have positive effect on Obama vote.  The positive effect is decreasing with increase of age.

17. Obama vs. Religion  Christian voters tend not to vote Obama, but not significant.  Jewish voters are supportive to Obama.

18.  Highly educated voters tend to vote Obama. Obama vs. Education Bachelor (%)

19. Obama vs. Unemployment  Jobless voters seem to be supportive to Obama, but the coefficient is not significant. Unemployment (%)

20. Obama vs. Income Income $  Voters with higher income are supportive to Obama.

21. Obama vs. Financial Status  Voters with higher income and less energy consumption are supportive to Obama.  Coefficients on Homeowner and Unemployment are not significant.

22. Conclusions  Surprising results  Voters with higher income are supportive to Obama.  Coefficient for African American voters is lower than expected  High energy users and home owners were not supportive  Surprising results  Voters with higher income are supportive to Obama.  Coefficient for African American voters is lower than expected  High energy users and home owners were not supportive

23. More Conclusions  Expected results  Women  Younger people  Educated people  Minorities  Expected results  Women  Younger people  Educated people  Minorities