be as follows: find 25 African American males, 25 European American males, 25 African American females, and 25 European American females. You use convenience sampling to find the people; the key is make sure you have the right number of people for each group quota.
Third is (i.e., specify the characteristics of your population of interest and locate individuals who match those characteristics). For example, you might decide that you want to only include "boys who are in the 7th grade and have been diagnosed with ADHD" in your research study. You might try to find 50 students who meet your "inclusion criteria" and include them in your research study.
The fourth type of nonrandom sampling is (i.e., each research participant is asked to identify other potential research participants who have a certain characteristic). You start with one or a few participants, ask them for more potential participants of a certain type, find those, ask them for some more, and continue this process until you have a sufficient sample size. This technique is used for selecting hard to find populations (e.g., where no sampling frame exists). For example, you might use snowball sampling if you want to do a study of people in your city who have a lot of power in the area of educational policy making (in addition to the well known positions of power, such as school board members and the superintendent).
Random Selection and Random Assignment
In you select a sample from a population using one of the random sampling techniques discussed earlier.
Your purpose is to obtain a sample that represents the population.
If you use a EPSEM technique, the resulting sample will be like a "mirror image" of the population, except for chance differences.
For example, if you randomly select (e.g., using simple random sampling) 1000 people from the adult population in Ann Arbor, Michigan, the sample will look like the adult population of Ann Arbor.
In , you start with a set of people (you already have a sample, which very well may be a convenience sample), and then you randomly divide that set of people into two or more groups (i.e., you take the full set and randomly divide it into subsets).
Your purpose it to produce two or more groups that are similar to each other on all characteristics.
You are taking a set of people and randomly “assigning” them to two or more groups.