Β1 Week 2 Accounting Research Questions

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The Data In order to answer the research question, I collected data to define and actualize the variables of interest. The first order of business was to collect data on the dependent variable, CEO total compensation. After selecting thirty-seven of the top Fortune 100 companies and identifying each company’s CEO, I was ready to begin collecting. The Securities and Exchange Commission’s EDGAR system provided a perfect source for the best identification of each CEOs total compensation. Every company must provide an annual proxy statement, labeled DEF 14A, which contains a summary compensation table of the top five earners. In every company examined, the CEO happened to fall into that category, as expected. Total compensation includes salary, stock incentives, bonuses, and other compensation. To simplify the data, I converted CEO compensation in millions of dollars. Although the summary compensation tables include earnings from the last three years, I chose the total compensation paid to each CEO at the end of the 2015 fiscal year. The next data collected was the average …show more content…

An F-test assesses the overall fit of the model by accounting for all of the independent variables in a single hypothesis test. The null hypothesis in this test is that β1=β2=β3=0, with my goal being to reject the null hypothesis, meaning my independent and dependent variables correlate. If the F-statistic is greater than the F-critical value, I will reject the null hypothesis. Discovered in an F-table, the F-critical value was found to be 2.89. In my regression, I calculated the F-statistic to be 3.415, which can be found in the Appendix. With the F-statistic being above the F-critical value, I reject the null hypothesis, showing that there is a correlation between my independent variables and CEO

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