Discussion: Descriptive Statistics
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. (attached)
Think of a specific purpose(s) for using descriptive statistics in your selected organization. (NEW HARBOR NORTH HS organization information attached)
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.
DISCCUSION QUESTION:
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.
RESOURCES:
https://mste.illinois.edu/hill/dstat/dstat.html
https://journals.sagepub.com/action/saml2post
https://journals.sagepub.com/doi/pdf/10.1177/0899764013508009