You will need to examine two of the nine sections of data, one section of qualitative data and one section of quantitative data, from the provided Unit 1 data set. Each section should include all data points. After analyzing your data, it will be necessary to write up a single concise professional report in Word that includes numerical data and graphs. The requirements include providing the data you selected, discussing why the data was selected and what was learned by examining these sets of data. Your analysis should include using Excel to obtain information about the data through the use of three measures of central tendency (mean, median, mode) and 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. If a measure is not applicable, then explain why. You will have to also provide 1 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. You will then need to discuss what you additionally learned from the results of this process. Explain why charts/graphs are important in conveying information in a visual format and why standard deviation and variation are important. Finally, you will need to combine all of the items above into one comprehensive report. This report must be completed in Microsoft Word and should contain:

An Introduction

The data selected

Discussion (Why you selected your data and what you learned by examining your selected data set.)

The measures of central tendency and variability. (Copy and paste from your Excel process.)

The charts/graphs

Summary (what you learned and why the processes are important.)

PROJECT 2: 2 AND A HALF PAGES

Using Excel as your processing tool, work through three simple regression analyses.

1. First run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the INTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

2. Next, run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the EXTRINSIC job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

3. Next, run a regression analysis using the BENEFITS column of all data points in the AIU data set as the independent variable and the OVERALL job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

4. Finally, make very specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?