Statistical Sampling

In order to generalize the results of a study to a larger population, data must be collected from a sample which is sufficiently large and is representative of the population. Simple Random Sampling (SRS) is the most basic and common approach to sampling. Researchers select the sample from a list of all members of the population through a process that ensures equal chances of selection. Unfortunately, SRS can be inefficient in many cases—it can be overly expensive and imprecise. For instance,

• Additional information is often available to the researchers that, if used properly, can result in more precise estimates of population characteristics.
• The proximity of population members to the researcher can affect data-collection costs by making the costs vary across population members.
• The population may naturally be clustered into homogeneous or heterogeneous groups.
• The researchers may also be interested in drawing conclusions about subpopulations.

In these cases and in others, SRS is no longer an efficient way of selecting a representative sample from a defined population. The data collection process must be fine-tuned with more advanced survey designs to maintain costs and increase precision. Our trained statisticians at Elite Research can help you determine appropriate sample sizes and design a more efficient data-collection scheme that will match your research needs while balancing precision and cost.

Feel free to contact Elite for more information about how we can help you with statistical sampling or about our other data collection services. Call us at 1-972-538-1374 (or tool free at 1-800-806-5661) or email us at This email address is being protected from spambots. You need JavaScript enabled to view it..

I was pleased to have Elite Research support my research work. Their service was prompt and reliable - always meeting my various deadlines and needs. [My Elite Research consultant] and the team are very professional in their approach to the work. I highly recommend their services for anyone conducting serious research.

Michael Simmons, PhD
Texas Woman's University