You have received the following dataset containing information on your Fortune 500 company's wages for employees in different positions and locations across the country. The dataset contains a number of different variables. These variables include the average hourly wage of the employee (WAGE), the education level of the employee and their years of experience (EDUCATION AND EXPERIENCE), it also contains their tenure with the company, race, gender, marital status and number of dependents (TENURE, RACE, GENDER, MARRIED, and DEPENDENTS), as well as whether or not they are located in an urban or a rural facility (URBAN).

As an analyst working for your Fortune 500 company, you have been tasked with organizing, analyzing and interpreting this dataset in order to determine the relationship between hourly wages and the other variables of interest provided in the dataset.

Task One: Data Organization and Summary

After labeling the types of variables in your dataset, summarize each variable using an appropriate graphical or tabular technique. This would include the most relevant use of a frequency distribution table, histogram, bar chart, or pie chart to best display and summarize each variable in your dataset. There should only be ONE table or graph summarizing each variable.