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Project: American Community Survey

Script learning project on American Community Survey

Term: Spring 2016, First project

Following suggestions by RICH FITZJOHN (@richfitz). This folder is orgarnized as follows.

proj/
├── lib/
├── data/
├── doc/
├── figs/
└── output/

Please see each subfolder for a README file.

Project Website: https://github.com/TZstatsADS/ProjectACS-s16c1t3-Look_at_Income

Team Members: Bob Minnich, Yueying Teng, Yusen Wang, Tianhong Ding

Project 1 - Team 3

Team members: Bob Minnich, Yusen Wang

Summary: In this project, we investigated the American Community Survey and the affects of Location, Age, Sex, Race,Secondary Education, Disability, Work Hours and Travel Time on Personal Income.

[Contribution Statement]

Bob Minnich contributed with the following:

  • Investigated Density Plot Comparisons Between multiple races looking at Minutes Traveled to Work, Work Hours Per Week and Personal Income.
  • Used weights to determine the population means, averages, standard deviations to allow statistical comparisons of races vs the population statistics
  • Looked at differences between Male and female within all of these splits
  • Used linear regression to solidify inferences made from visual plots by confirming effects of race and sex on Income within the United States.
  • Assisted with bubble plot naming of jobs when using mouse hover Compiled report and prepared presentation.

Yusen Wang contributed with the following:

  • Focused on finding how gender and age influence income within the United States.
  • Used polygon plot to compare males' and females' income.
  • Analyzed skewness and tail of males' and females' income density distribution in a log scale.
  • Split people who have income records into different groups based on age.
  • Used polygon plot to analyze similarities and differences among all groups.
  • Drew boxplot to show income of every age to prove previous findings.

Yueying Teng contributed with the following:

  • Proposed the topic of income analysis and worked with the rest of the team to identify the variables of interests.
  • Investigated the influence of geographical factors such as birth place and place of residence on average personal income.
  • Used googleVis to visualize average personal income according to birth place and state of residence.

Tianhong Ding contributed with the following:

  • Explored the topic such as people's residence are related to their orginal nationality.
  • Investigated the relationship between people's income and their first entry into the field. Use bubble plot to visualize it.
  • Investigated the relationship between people's income and disbility. Use Bar plot to visualize it.

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