In statistical investigation, the investigator usually deals with the general magnitude and the study of variation with respect to one or more characteristics relating to individual belonging to a group. The group of individuals under study is called population or universe. Population is an aggregate or collection of objections, animates or inanimate defined according to characteristics under study. The population may be finite or infinite.
Complete enumeration of all units of the population is called census. In any statistical investigation, complete enumeration is not practical.
In a statistical investigation, the interest usually lies in the assessment of the general magnitude and the study of variation with respect to one or more characteristics relating to individuals under study is called population or universe. Thus, in statistics, population is an aggregate of objects under study.
It is obvious that for any statistical investigation, complete enumeration of the population is rather impractical. For example, if we want to have an idea of the average per capita (monthly) income of the people of Nepal, we will have to enumerate all the earning individuals in the country, which is rather a very difficult task.
If population is infinite, complete enumeration is not possible. Also, if the units are destroyed in the course of inspection, 100% inspection is not taken because of multiplicity of cause viz. administrative and financial implications, time factors etc. and we take the help of sampling.
The method of enumerating each and every unit of population is known as census. Some of the examples are population census, manufacturing census, agricultural sample census etc.
A finite subset of statistical individuals in a population that is used to represent that population is called a sample and the number of individuals in a sample is called sample size. For the purpose of determining population characteristics, instead of enumerating the entire population, the individual in the sample only are observed. Then, the sample characteristics are utilized to approximately determine or estimate the population. For example, on examining the sample of a particular stuff, we arrive at a decision of purchasing or rejecting the stuff.
Sampling is more often used in our daily life. For example, in a shop, we assess the quality of sugar, wheat or any other commodity by taking a handful of it from the bag and then decide to purchase it or not. A housewife normally tastes the cooked products to find if they are properly cooked and contains the proper quantity of salt.
The survey carried out by selecting representative sample of the study population is known as sample survey. For example, Nepal living standard survey, family planning survey etc.
The population units selected as a sample from the population is called sampling unit. It is individual item in the sample. For example, a house, a college, a district, a city, an individual etc.
Sampling frame is the list of all the elements that are in the population. When the population is defined according to the characteristics under study, it is known as a frame consisting of the sampling units in the population. It is used to select sample units from the population as a sample. Frame or the list may not be readily available in practice, so it has to be prepared for the selection of the sample before conducting the main survey.
It should be exhaustive, up-to-date and should consist of all the information about the units so that an appropriate sample design may be planned. It should be suitable for the coverage of the study and should be restored by reliable sources. It should be free of errors like repeated units, missing elements, non-coverage, incompleteness, clustering of elements, blanks, foreign elements etc. The effective way of solving the frame problems is to correct the entire population list or redefine the population to fit the frame or ignore and discard the problem if it cannot be fixed.