What it Takes to Make History - PowerPoint PPT Presentation

jaden
what it takes to make history l.
Skip this Video
Loading SlideShow in 5 Seconds..
What it Takes to Make History PowerPoint Presentation
Download Presentation
What it Takes to Make History

play fullscreen
1 / 23
Download Presentation
What it Takes to Make History
305 Views
Download Presentation

What it Takes to Make History

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. What it Takes to Make History 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

  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.

  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?

  5. Why are we studying the election? • 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

  7. Brief Summary • 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

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

  10. Descriptive Statistics cont. • 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

  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 Minority Blacks DC DC Minority (%) Blacks (%)

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

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

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

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

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

  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

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