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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.

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Presentation on theme: "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."— 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 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


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