Type of Sampling 
When to use it 
Advantages 
Disadvantages 
Probability Strategies 



Simple Random Sampling 
When the population members are similar to one another on important variables 
Ensures a high degree of representativeness 
Time consuming and tedious 
Systematic Sampling 
When the population members are similar to one another on important variables 
Ensures a high degree of representativeness, and no need to use a table of random numbers 
Less random than simple random sampling 
Stratified Random Sampling 
When the population is heterogeneous and contains several different groups, some of which are related to the topic of the study 
Ensures a high degree of representativeness of all the strata or layers in the population 
Time consuming and tedious 
Cluster Sampling 
When the population consists of units rather than individuals 
Easy and convenient 
Possibly, members of units are different from one another, decreasing the techniques effectiveness 
NonProbability Sampling 



Convenience Sampling 
When the members of the population are convenient to sample 
Convenience and inexpensive 
Degree of generalizability is questionable 
Quota Sampling 
When strata are present and stratified sampling is not possible 
Insures some degree of representativeness of all the strata in the population 
Degree of generalizability is questionable 
Notes:
1. Reducing sampling error is the major goal of any selection technique.
2. A sample should be big enough to answer the research question, but not so big that the process of sampling becomes uneconomical.
3. Estimating sample size – in general, you need a larger sample to accurately represent the population when:
a. The amount of variability within groups is greater, and
b. The difference between the tw groups gets smaller.
4. In general, the larger the sample, the smaller the sampling error and the better job you can do.
5. If you are going to use several subgroups in your work (such as males and females who are both 10 years of age, and healthy and unhealthy urban residents), be sure your initial selection of subjects is large enough to account for the eventual breaking down of subject groups.
6. If you are mailing out surveys or questionnaire, count on increasing your sample size by 40% to 50% to account for lost mail and uncooperative subjects.
7. Remember that big is good, but appropriate is better. Do not waste your hardearned money or valuable time generating samples that are larger than you need… law of diminishing returns will set in!