CHES (Certified Health Education Specialist) Practice Exam 2025 – Your All-in-One Guide to Exam Success!

In a stratified random sample, the first step taken is to divide the survey population into strata. This process involves categorizing the population into subgroups that share similar characteristics, such as age, gender, income level, or any other relevant factors. The purpose of this stratification is to ensure that the sample accurately reflects the diversity within the population, allowing for more precise and reliable results in research findings.

By organizing the population into these distinct strata, researchers can then randomly select participants from each subgroup. This method enhances the representativeness of the sample and reduces potential biases that could arise from selecting individuals haphazardly from the entire population. It ensures that each subgroup is adequately represented in the final analysis, leading to more meaningful insights and conclusions in health education and other research applications. Other options, such as performing background checks or identifying volunteers, do not align with the foundational steps of creating a stratified sample. Random selection without criteria also does not address the stratification necessary for this sampling technique.