Excerpt
Outline
1. Introduction to Key terms and Concepts
a.Human Capital Theory
b.Screening Hypothesis
c.Employment
i. Public Employment
ii. Private Employment
iii. Self Employment
d.Statistical Tests Used
i. Mean
ii.Standard Deviation
iii. T-test
iv. F-test
v.Chi-Square
2. Summary of the Article/Study
3. Research Design
4. Discussion
a.Strength (s)
b.Critic (s)
5. Recommendations
6. Relevancy in Education Settings
7. References
Defining the Key Terms
- Human Capital Theory is fundamental theory in the field of Education Economics. This theory expounds that people’s learning capacities (education levels) are comparable to other natural resources in the production process. When these capacities are exploited effectively can result into benefits both at enterprise and society levels (Galabawa, 2005; Livingstone, 1997).
- Screening Hypothesis is a tentative theory that suggests that inter-educational earnings differentials, even when standardized for differences due to non- educational factors, reflect no direct productivity-enhancing effects of education but only its effects as a device for signaling preexisting ability differences (Layard and Psacharopoulos, 1974).
- Employment is a contract between two parties, one being the employer (public or private) and the other being the employee. However, when an individual entirely owns the business for which he or she labors, this is known as self-employment (Wikipedia, 2011).
- Mean also Arithmetic mean as often used in statistics, the term refers to the average of a set of values (i.e., numbers, cars, people e.t.c) or distribution (i.e., ge range, financial income). As well as statistics, means are often used in geometry and analysis (Wikipedia, 2011). The Mean is denoted by X .
- Standard deviation is a widely used measure of variability or diversity used in statistics and probability theory. It shows how much variation or "dispersion" there is from the average (mean, or expected value). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data points are spread out over a large range of values. This statistic measure is denoted by SD (Wikipedia, 2011).
- T-test is the most commonly used method to evaluate the differences in means between two groups. For example, the t -test can be used to test for a difference in test scores between a group of patients who were given a drug and a control group who received a placebo (Statsoft, 2011).
- F-test is any statistical test in which the test statistic has an F-distribution under the null hypothesis. It is most often used when comparing statistical models that have been fit to a data set, in order to identify the model that best fits the population from which the data were sampled (Wikipedia, 2011).
- Chi-square also referred to as chi-squared test or χ2 test, is any statistical hypothesis test in which the sampling distribution of the test statistic is a chi-square distribution when the null hypothesis is true, or any in which this is asymptotically true, meaning that the sampling distribution (if the null hypothesis is true) can be made to approximate a chi-square distribution as closely as desired by making the sample size large enough (Wikipedia, 2011).
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- Quote paper
- Yazidu Saidi Mbalamula (Author), 2014, Education and Employment Status: A Test of the Strong Screening Hypothesis in Italy, Munich, GRIN Verlag, https://www.grin.com/document/271538
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