The data set for the study is a sample of a survey conducted on the population of the American Intellectual Union (AIU). It is available via the following link: Excel 2007 DataSet with DataSet Key which contains the following nine sections of data that will be used throughout our course:

o Gender
o Age
o Department
o Position
o Tenure
o Overall Job Satisfaction
o Intrinsic Job Satisfaction—Satisfaction with the actual performance of the job
o Extrinsic Job Satisfaction—external to the job, for example, office location, your work colleagues, your own office (cubicle/hard walled office, etc),
o Benefits—Health insurance, pension plan, vacation, sick days, etc.
In the first assignment you are to complete the following:
• You will need to examine two of the nine sections of data:
o one section of qualitative data (choose either Gender or Position)
o one section of quantitative data (choose either Intrinsic or Extrinsic)
• Each section should include all data points listed in the column for the variable. The requirements include:
1. Identify the data you selected.
2. Explain why the data was selected.
3. Explain what was learned by examining these sets of data.
4. Your analysis should include using Microsoft Excel to obtain information about the data through the use of three measures of central tendency (mean, median, mode).
5. Your analysis should also include the use of two measures of variability (standard deviation and variance). Some measures are appropriate for qualitative data, and some are appropriate for quantitative data.
6. If a measure is not applicable, then explain why.
7. You will have to also provide one chart/graph for each of the results of the two processed sections of data (2 total), such as a pie or bar chart or a histogram. (A table is not a chart/graph.) Ensure that you label the chart/graph clearly.
8. You will then need to discuss what you additionally learned from the results of this process.
9. Explain why charts/graphs are important in conveying information in a visual format and why standard deviation and variation are important.

What have you done so far?