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Conduct a simple linear regression analysis to examine the relationship between 'education' (the independent variable) and 'wages' (the dependent variable). Using the Excel data file, prepare a 1200 word report using the following structure:
Purpose (2 marks)
In this section, the purpose of the report needs to be clearly and concisely stated.
Background (4 marks)
In this section, write a brief overview on the association between education and earnings. Why would economists be interested in this particular issue?
Method (4 marks)
In this section, provide an overview of the empirical approach used to examine the association between education and wages.
Results (20 marks)
In this section, you need to present and summarize the results from your statistical analysis. In particular, the result sections must:
∙ Provide a descriptive analysis of the two variables (e.g., mean, standard deviation, minimum and maximum). (2 marks)
∙ Develop a scatter diagram with education as the independent variable. What does the scatter diagram indicate about the relationship between the two variables? (3 marks)
∙ Estimate a regression equation that can be used to predict the wages given the level of education. (2 marks)
∙ State the estimated regression equation and interpret the meaning of the slope coefficient. (3 marks) ∙ Is there a statistically significant association between education and wages? What is your conclusion?(2 marks)
∙ Did the regression equation provide a good fit? Explain. (3 marks)
∙ Calculate the predicted wages for a person with 12 and 14 years of education, respectively. What is the difference in hourly wage rate? (5 marks)
Discussion (5 marks)
In this section, provide a brief overview of the results. What are the key strengths and limitations of this analysis? (e.g., data, method, etc.). How do the results from this analysis compare with other studies? (e.g., are the findings consistent?). Do these findings have clear policy implications?
Recommendations (5 marks).
In this section, you should present three well-considered recommendations.
The main aim of this report is to determine the relationship between education and wages. A simple linear regression analysis has been utilized for examining the relationship between the independent variable (Education) and the dependent variable (Wages). The report also presents recommendations based on findings of statistical analysis.
All individuals possess a unique set of abilities and skills, which can be transformed into human capital after training them for skill development and providing them adequate education (Johnson, 2009). Education can be considered as an investment in the human capital as it aims to improve the skills of the workers and enhance their productivity. The higher the level of education attained by a person; more is his/her earning capacity. This shows that there is a direct relationship between education and earning. Even companies provide educated individuals a better salary. According to the statistics provided by OECD in 2015, the workers in Australia possessing a Bachelor's degree earned 81% more money than the ones who just had a high school diploma, and 125% more than the ones without any high school diploma (OECD, 2015). The research by Tamborini, Kim, and Sakamoto (2015) also indicated that educated individuals have a high lifetime earning whereas, the individuals who are not educated are not able to earn much in their lifetime, in most cases. Economists must be interested in exploring this topic because finding of this research can enable them in improving the economic growth rate of nation. The findings may also help the government to understand importance of education and draft policies aimed at enhancing the literacy rate. The increased rate of literacy will improve the economic conditions of people as well as the entire nation.
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