Descriptive statistics provide a snapshot of variables. They describe quantitative data by presenting the average or typical case. These types of descriptive statistics are called measures of central tendency. You can also describe data by showing how much the cases are spread out or clustered together. These types of statistics are called measures of dispersion. Measures of central tendency and measures of dispersions can be useful descriptors on their own, or they can be used as “building blocks” for more advanced statistics.
Neither approach (measures of central tendency or measures of dispersion) is superior to the other. They are often used in combination with each other to provide a fuller description of variables. For this week’s Discussion, you will consider which type of descriptive statistics (measures of central tendency or measures of dispersion) would be useful in describing the information you need to evaluate the program, problem, or policy you selected for your Final Project.
For this Discussion:
- Review Chapter 12 in your course text, Research Methods for Public Administrators, paying particular attention to the section on “Characteristics of a Distribution.”
- Review the article, “Introduction to Descriptive Statistics,” paying particular attention to examples of descriptive statistics.
- Think of a specific purpose(s) for using descriptive statistics in your selected organization.
- Consider why descriptive statistics would be used for this purpose(s).
- Consider the type(s) of descriptive statistics you might use, and whether the use of other descriptive statistics, might be valuable for this purpose.
Review the Learning Resources for this week. Consider the types of descriptive statistics that would help answer your research question.
Post a description of the descriptive statistics that might work well for the Evaluation Design in your Final Project. Explain how these statistics could be used, and justify why they are appropriate.
- Johnson, G. (2014). Research methods for public administrators (3rd ed.). Armonk, NY: M. E. Sharpe.
- Chapter 12, “Data Analysis for Description” (pp. 171–185)
- Taber, D. R., Chriqui, J. F., Powell, L., & Chaloupka, F. J. (2013). Association between state laws governing school meal nutrition content and student weight status: Implications for new USDA school meal standards. JAMA Pediatrics, 167(6), 513–519.
Association between state laws governing school meal nutrition content and student weight status: implications for new USDA school meal standards by Taber, D. R., Chriqui, J. F., Powell, L., & Chaloupka, F. J. in JAMA Pediatrics, 167(6), 513-519. Copyright 2013 by American Medical Association.
Reprinted by permission of American Medical Association via the Copyright Clearance Center.
- Carnochan, S., Samples, M., Myers, M., & Austin, M. J. (2013). Performance measurement challenges in nonprofit human service organizations. Nonprofit and Voluntary Sector Quarterly.
Performance measurement challenges in nonprofit human service organizations by Carnochan, S., Samples, M., Myers, M., & Austin, M. J. in Nonprofit and Voluntary Sector Quarterly, [online]. doi: 10.1177/0899764013508009. Copyright 2013 by Sage Publications. Reprinted by permission of Sage Publications via the Copyright Clearance Center.
- Hill, J. (n.d.). Introduction to descriptive statistics. University of Illinois, Mathematics, Science and Technology Education. Retrieved June 7, 2014, from http://mste.illinois.edu/hill/dstat/dstat.html