6.1 How to Use Stratified Sampling
Now that we have chosen to sample 40 male and 60 female students, we still need to select these students from our two lists of male and female students see STEP FOUR above.
If we wanted to look at the differences in male and female students, this would mean choosing gender as the stratification , but it could similarly involve choosing students from different subjects e. Use a simple random or systematic sample to select your sample. So there will be half as many explicit strata as there are achieved cases. Suppose a research team wants to determine the GPA of college students across the U. The small group is referred to as a sample size , which is a subset of the population that is used to represent the entire population.
How to Use Stratified Sampling STAT
This would create a skewed sample that would bias the research and render the results invalid. References in periodicals archive? The firm decides to select 20 households from Town A, 8 households from Town B and 12 households from the rural area. Added to your Shopping Cart! Views Read Edit View history. The county has two towns, A and B, and a rural area C.
Personal Finance. If the respondents needed to reflect the diversity of the population, the researcher would specifically seek to include participants of various minority groups such as race or religion, based on their proportionality to the total population as mentioned above.
Sampling stratified cluster Standard error Opinion poll Questionnaire. In this case sampling may be stratified by production lines, factory, etc. Dictionary browser? Proportionate stratified sampling almost always leads to an increase in survey precision relative to a design with no stratification , although the increase will often be modest, depending upon the nature of the stratifiers. Unequal Probability Sampling Lesson 4: For instance, if your four strata contain , , , and people, you may choose to have different sampling fractions for each stratum.
The main advantage of stratified random sampling is that it captures key population characteristics in the sample.
What's an example of stratified random sampling?
It depends on the relative sampling fractions and on how the variability of the survey responses differs in the different strata. The effect of disproportionate stratification on overall estimates for the population will depend on a variety of factors. There are households in town A, 62 in town B and 93 in the rural area, C.
Related topics. The results are given in the following table: Comprehensive school counseling programs and student achievement outcomes: The formula are computed differently according to the sampling scheme within each stratum. For surveys that want to estimate the porportion of certain types of respondent this means reducing the sampling fraction when the types of interest is uncommon.
Instead if we choose to take a random sample of 10, 20 and 30 from Town A, B and C respectively then we can produce a smaller error in estimation for the same total size of sample.