Apply Quantitative Reasoning

Now that you have completed your analysis, think about the patterns you’ve seen in the workforce.

1. From the created histogram, it appears that a large share of employees have a salary between $31,000—$40,000 or $51,000—$60,000. This may indicate reasonable promotion rate for new employees. Is this distribution unimodal or bimodal? Explain.

2. The line chart, as detailed in your "Graph Charts" Excel spreadsheet, shows sales increasing over the years, after an initial few rocky years from 1999 to 2002. In 2015, sales slightly decreased to under $4,000,000. Investors want to know what the projected sales will be in 2017. One method for determining this value is to calculate the average percentage growth, based on historical trends. For example, if sales were $200 last year and $500 this year, the average percentage growth between these years was 150%. ((500-200)/200)*100. Calculate the average percentage growth for 2002–2015 and projected sales for 2016 and 2017.

3. The standard deviation provides insight into the distribution of values around the mean. If the standard deviation is small, the more narrow the range between the lowest and highest value. That is, values will cluster close to the mean. From your descriptive statistics, describe your standard deviations. What does this tell you about the variables?

4. The company has a keen interest in the educational, race, and gender makeup of its workforce. Its emphasis is on a diverse, dynamic workforce. From your "Graph Charts" spreadsheet, describe your pie chart findings for these characteristics of the workforce. Describe how you would determine if the company was meeting expectations on these characteristics.

5. The company is conducting an analysis on how many positions to create to keep up with demand. Specifically, it wants to know an estimate of the number of positions per job title. From your Excel chart, identify the mode of the job title distribution. Describe your findings.

6. Now that you have done all the work with data, you will write a short three- to four-paragraph summary of your analysis. This is important. While you have done a wonderful job with your analysis, you can never assume that the end user will be able to interpret the data the way it should be understood. Supporting narrative is helpful. Never simply provide a "raw data" dump. Instead, seek to provide information!

a. Write a one-paragraph narrative summary of your findings, describing patterns of interest.

b. Provide an explanation of the potential relevance of such patterns. c. Provide a description of how you would investigate further to determine if your

results are "good or bad" for the company.

Prepare your response in this workbook. Create a tab for QR Analysis, create a text box, and paste your answers to the above questions in it. Move the tab to the first tab position.

Structure your essay like this: