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Module 3 – SLPOBTAINING THE DATA FOR THE RESEARCH CONTEXT
Descriptive statistics are used to learn about the characteristics of a measure that is collected over time or may be a measure of an item from a survey administered to many people. Typically, descriptive statistics are the average score (mean), the maximum, the minimum in the scores along with the variation. Descriptive statistics is used to describe the measures rather than to make inference centered around the same item or conceptual construct being measured. Thus, descriptive statistics is not inferential statistics and does not use probability to infer behaviors of a population from which the measures were drawn.
Descriptive statistics fits the background analysis for your firm selected for your DSP. Here you have financial and performance measures of the firm with respect to others in the same competitive space. In most cases descriptive measures can be used to generate trend lines to try and forecast based on past measures.
Here is a descriptive spreadsheet for the United Way of Orange County that shows the average and standard deviation for revenues and expenses from the 990 Report we looked at in SLP 2. Here in this spreadsheet Figure 4 (click the image to open the file) you see by clicking the various tabs on the lower part of the spreadsheet graphs that can be generated from this 990 data. Columns F and G have the average and standard deviation of the revenue and expense measures, but they are rather static. To use the years of revenue and expense measures, you can click the Forecast Sheet tab on your tool bar. This is how the graphs for Revenues, Expenses, and Net were produced where a technique called exponential smoothly is used that factors in the four years of data to produce the trend lines in the forecast.
Chapter 18 in:Carlberg, C. (2016). Excel sales forecasting for dummies, 2nd edition. John Wiley & Sons. Available in the Trident Online Library.
SLP Assignment Expectations
Now examine the secondary data you have on your firm from SLP 2 or add more to the data as needed. Look at the sample and review the Excel book and particularly the one on Exponential Smoothing. Calculate some descriptive statistics for your data and prepare some forecast charts. Remember the Forecast Sheet tool on the upper toolbar next to What If Analysis. Produce a spreadsheet with associated graphs; also provide a page or two to discuss this data analysis and the conclusions you have drawn. Add this to the growing work you have on the Background for the firm you are studying.
Your assignment will be graded using the following criteria:
Assignment-Driven Criteria: Student demonstrates mastery covering all key elements of the assignment.
Critical Thinking/Application to Professional Practice: Student demonstrates mastery conceptualizing the problem and analyzing information. Conclusions are logically presented and applied to professional practice in an exceptional manner.
Business Writing and Quality of References: Student demonstrates mastery and proficiency in written communication and use of appropriate and relevant literature at the doctoral level.
Citing Sources: Student demonstrates mastery applying APA formatting standards to both in-text citations and the reference list.
Professionalism and Timeliness: Assignments are submitted on time.