Statistical sampling deals with certain groups, such as elementary school students.
Statistical sampling refers to the study of populations by collecting information and analyzing it. It is the basis for a great deal of information, ranging from estimates of the average height in a country to studies on the impact of marketing on children. Numerous professions use statistical sampling, including psychology, demography, and anthropology. However, like any study method, this method is subject to error and it is important to review the methods used to conduct a study before accepting the results.
This process begins with the definition of the population that the scientist wants to study and the variable that he wants to measure. For example, someone might want to know the average weight of elementary school children. The scientist then decides how to collect the desired data. In the example above, the scientist might travel to schools with a scale, send questionnaires to doctors or parents, or try to access school health records. Many researchers try to measure directly, rather than relying on automatic responses, because that way the results are consistent.
Once the population, the variable being measured, and the method have been defined, the scientist decides how to accurately sample the population so that the data collected is representative of a larger group. In other words, statistical sampling does not imply measuring the desired variable in each individual of the study population; a selection of individuals is used to generalize the results. In general, the larger the sample size, the better the results.
The most common system is random sampling, in which a scientist generates a list of individuals at random from a central database. Some scientists use cluster sampling, where a population is divided into a group of small clusters and each cluster is studied extensively. Others may use systematic sampling, where every nth person in the population is studied. The most dangerous and unreliable selection system for statistical sampling is convenience sampling; someone standing on a street corner with surveys is using convenience sampling, which can give very inaccurate results.
Once the data is collected, the researcher analyzes it and uses it to make generalizations about a population. In studies that rely on statistical sampling, the method used is often clearly spelled out so that other scientists can decide whether or not the method is valid. An invalid method can cause sampling error, which would call into question the results of the study.