Occupational Employment Analysis for 2012
Document Type
Oral Presentation
Campus where you would like to present
SURC 202
Start Date
16-5-2013
End Date
16-5-2013
Abstract
Getting a degree in college has been shown to increase an individual’s income, but there are a great many degrees to choose from. Deciding a major in college can be one of the most important decisions one makes, and future income is a key factor in making that decision. With this dataset, I use data from the Bureau of Labor Statistics to analyze occupational employment in the United States. The data include geographic area, industry, occupation, total employment, and data for both hourly and annual wages. In the presentation, I will be going through the dataset and showing the differences in wages and unemployment based on the different industries and occupations. I run statistical tests, including regression, discriminant analysis, and t-tests to explore correlation among the data. Presenting this data should give the audience an idea of what jobs are the best paying today and in what industries those jobs can be found.
Recommended Citation
Rindlisbacher, Nathan, "Occupational Employment Analysis for 2012" (2013). Symposium Of University Research and Creative Expression (SOURCE). 105.
https://digitalcommons.cwu.edu/source/2013/oralpresentations/105
Additional Mentoring Department
Mathematics
Occupational Employment Analysis for 2012
SURC 202
Getting a degree in college has been shown to increase an individual’s income, but there are a great many degrees to choose from. Deciding a major in college can be one of the most important decisions one makes, and future income is a key factor in making that decision. With this dataset, I use data from the Bureau of Labor Statistics to analyze occupational employment in the United States. The data include geographic area, industry, occupation, total employment, and data for both hourly and annual wages. In the presentation, I will be going through the dataset and showing the differences in wages and unemployment based on the different industries and occupations. I run statistical tests, including regression, discriminant analysis, and t-tests to explore correlation among the data. Presenting this data should give the audience an idea of what jobs are the best paying today and in what industries those jobs can be found.
Faculty Mentor(s)
Dominic Klyve