RES/341 Research and Evaluation I
University of Phoenix
Begin your introduction here. Barbara
Summarize Peer-Reviewed Articles
The article, Decomposing the Education Wage Gap: Everything but the Kitchen Sink” talks in length about the erosion of “wages ranging from both time and educational status. Their results confirm the importance of investments in and use of technology” (Hotchkiss & Shiferaw, 2011, p. 1). The authors Hotchkiss and Shiferaw also show that demand and supply factors played very different roles in the growing wage gaps between the 1980s and 1990s.
For example, the labor market looked at two separate sectors; one for skilled workers and the other for individuals with fewer skills. This article suggests numerous supply and demand reasons for the growth in the wage gap primarily because of technological changes and skill- biased technological changes. The authors also discusses how the demand for skilled labor increases, as the returns to a college education should also increase, which, in turn, should lead to an increase in the supply of educated workers, which should put downward pressure on the skills wage gap which is unfortunately not the case (Hotchkiss & Shiferaw, 2011, p. 1.). Describe How Articles Apply to the Research
Like this article, information provides will demonstrate a clearer understanding of the related differences of various industries supply and demand factors that help explain the growing earnings inequality between education levels, gender, experience, and etcetera. The research will explore the nature and origins of wage differences between men and women of various backgrounds. Consideration factors include such items as the high wages of a few White men, and gendered patterns of occupational and educational choice and work experience. White men are not the only group that out-earns women, although the wage gap is largest between white men and white women, and within other groups, such as African Americans, Latinos, and other races like Asians. Sampling Design
Population in statistics refers to “the entire collection of items that is the focus of concern” (Hoffman, 2002, p. 1). The primary focus of concern in the wages and wage earners data set focuses on the wage gaps between populations with education and populations without higher education. Education has many definitions; some people believe that education is simply graduating from high school and others believe it means earning a bachelor’s degree or certificate from a trade school (Cantu, 2003). However, most people would agree that higher education leads to increased income. Education plays an important factor when considering wage gaps within a selected population. A close examination of the wages and wage earners data set will indicate if various levels of education have an influence on the wage gaps or not, and additional studies will indicate if men receive higher incomes than women The sample size of the population for the wage and wage earners data set consist of 100 people. From the data set, 54 people of the population consist of women and 46 are men. The wages earned for men and women rage from 9,879 to 83, 601 dollars with a median of 28, 815.50 dollars, and a sample standard deviation of 16, 947.10 dollars. From the data set, 62% of the people have 12 or fewer years of education, and 86% of the people have 12 years or more of education. Additionally, 22% of the people have 16 or more years of education. The data set breaks down the population by occupation and industry of work. For example a person’s occupation could be manufacturing, construction, or other, and the person’s occupation falls under one of five categories that include management, sales, clerical, service, professional, or other. The data also includes residency, nonwhite, Hispanic, years of work experience, married, age, and whether the person belongs to a union...
References: Barchard, K.A. (2003) Ethics in online data collection, Presentation at the Western Psychological
Cantu, R. (December 2003). Texas Labor Market Review. What is value of an education? Retrieved from: http://www.tracer2.com/admin/uploadedpublications/1042_tlmr0312art.pdf
Hoffman, H. (February 2002). Professor Emeritus of Phycology. Internet glossary of statistical terms. Retrieved from: http://www.animatedsoftware.com/statglos/sgpopula.htm
Hotchkiss, J. L., & Shiferaw, M. (2011). Decomposing the Education Wage Gap: Everything but the Kitchen Sink. Federal Reserve Bank Of St. Louis Review, 93(4), 243-271.
Northern Arizona University. (2001). Research & Evaluation in PRM. Module 2: Methods of Data Collection. Retrieved from: http://www.prm.nau.edu/prm447/methods_of_data_collection_lesson.htm
University of Phoenix. (2011). Wages and Wage Earners Data Set. Retrieved from https://ecampus.phoenix.edu/secure/aapd/ubam/res341/r4/DataSets/RES341r4Wage
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