Methods of Sampling
Most sampling methods can be categorized into two –
(A) Probability Sampling Methods
(B) Nonprobability Sampling Methods
(A) Probability Sampling Methods– Are those that clearly specify the probability or likelihood of inclusion of each element or individual in the sample.
Major Probability Sampling methods are the following-
- Simple Random Sampling
- Stratified Random Sampling
1.Simple Random Sample– A simple random is a one in which each and every individual of the population has an equal chance of being included in the sample and also the selection of one individual is in no way dependent upon the selection of another person.
2.Stratified Random Sample– In stratified random sampling the population is, first, divided into two or more strata, which may be based upon a single criterion such as gender- male and female, or upon a combination of two or more criteria such as gender and education, yielding four strata, namely, male undergraduates, male graduates, female graduates and female graduates. Having divided the population into two or more strata, which are considered to be homogeneous internally, a simple random sample for the desired number is taken from each population stratum.
(B) Nonprobability Sampling Methods- Are those in which there is no way of assessing the probability of the element or group of elements, of population being included in the sample. Important techniques of nonprobabilty sampling methods are-
- Quota Sampling
- Accidental Sampling
- Judgmental or Purposive Sampling
- Systematic Sampling
- Snowball Sampling
1.Quota Sampling– This type of sampling is apparently similar to stratified random sampling. Here, the investigator recognizes the different strata of population and from each stratum he selects the number of individuals arbitrarily. This constitutes the quota sample.
Suppose, the investigator knows that population of individual that he is going to study has three strata in terms of Shifts- Morning, Afternoon & Evening. Further suppose he knows that there are 100 people in Morning shift, 700 people in Afternoon shift and 200 people in Evening shift. Thus, the population consists 1000 individuals. If he wants to select 100 individuals & finally, selects 10 from Morning shift, 70 from Afternoon shift & 20 from Evening shift, according to his convenience ( and not randomly), this constitutes quota sample.
- Purposive Sample– This type of sample is based on the typicalityof the cases to be included in the sample. The investigator has some belief that the sample being handpicked is a very good representative of the population. A purposive sample is also known as judgmental sample because the investigator on the basis of is impression makes a judgment regarding the concerned cases, which are thought to be typical of the population.
Before the start of general elections, purposive samples are often taken in an attempt to forecast the national elections. The investigator selects the persons from those states whose election result on previous polls have approximated the actual result & thus, have been typical of the whole population.
- Accidental Sampling– It refers to a sampling procedure in which the investigator selects the persons according to his convenience. Here he does not care about including the people with some specific or designated traits, rather he is mainly guided by convenience & economy. This is a crude method of sampling & the investigator knows that little can be generalized from the sample thus drawn.
- Systematic sampling-This may be defined as drawing or selecting every nth person from the predetermined list of elements or individuals. Selecting every 5th roll number in a class of 60 students will constitute systematic sampling. Likewise, drawing every 8th name from a telephone directory is an example of systematic sampling.
- Snowball Sampling-This type of sampling is basically socio metric. It is defined as having all the persons in a group or organization identified their friends who in turn identify their friends and associates until the researcher observes that a constellation of friendships converges into some type of a definite social pattern. Snowball sampling has important research application in relatively small business & industrial organizations where N is expected not to exceed 100. Such sampling is more convenient to the studies of social change & diffusion of information among specific segments of social organizations.