Populations and Sampling

•Population is any group of individuals that has one or more characteristics in common and that are of interest to the researcher. It is a group of individuals with at least one common characteristic that distinguishes that group from other individuals.

 •A target population is the specific group of individuals to whom the findings of the research are proposed to generalize. 

 •Accessible populations are groups that are representative of the overall target population as well as convenient for the researchers. 

 •Sampling is the process of selecting a number of individuals for a study in such a way that the individuals represent the larger group (population) from which they were selected. The process of going from a large general population to a target population to a sample is common in behavioural sciences research.The purpose of sampling is to gain information about the larger population.The degree to which the selected sample represents the population is the degree to which the research results are generalizable to the population. •A Sample is a small representative proportion of the population that is selected for observation and analysis. 

 Sampling Methods 

 Randomness. The concept of randomness has been basic to scientific observation and research and is very crucial in the process of sampling. It is based on the assumption that while individual events cannot be predicted with accuracy, aggregate events can. Randomization provides the most effective method of eliminating systematic bias and of minimizing the effect of extraneous (unconnected, exterior, outside) variables. The principle of randomization is based on the assumption that through random assignment differences between groups result only from the operation of probability or chance. These differences are known as sampling error or error variance, and their magnitude can be established by the researcher. It is therefore, important to note that a random sample is not necessarily an identical representation of the population. Regardless of the specific techniques used, the steps in sampling include (i) identification of the population, (ii) determination of sample size, and (iii) selection of the sample. Sampling methods can be random (probability) as well as non-random (or non-probability). 

  I. Random/Probability Sampling In a probability/random sampling technique each and every individual of the population gets an equal and independent chance of selection as a sample. Random sampling is generally used in quantitative researches. It can be of following four types: 

 •Simple Random Sampling is the process of selecting a sample in such a way that all individuals in the defined population have an equal and independent chance of being selected for the sample. It is the best single way to obtain a representative sample. 

•Simple random sampling involves defining the population, identifying each member of the population, and selecting individuals for the sample on a completely chance basis. 

 •Lottery method can be used but it is more customary to use a table of random numbers to select the sample. 

 •Stratified Sampling is the process of selecting a sample in such a way that identified subgroups in the population are represented in the sample in the same proportion that they exist in the population. •Stratified sampling can also be used to select equal-sized samples from each of a number of subgroups if subgroup comparisons are desired. 

 •The steps in stratified sampling are similar to those in random sampling except that in stratified sampling, random sampling is done for each subgroup. 

 •Cluster Sampling is sampling in which groups, not individuals, are randomly selected. Clusters can be communities, states, school zones, etc. •Here, the random selection of groups or clusters is done (not of individuals). 

 •In both stratified and cluster sampling, multistage sampling is usually done. 

 •Systematic Random Sampling is sampling in which individuals are selected from a list by taking every Kth name, where K equals the number of individuals on the list divided by the number of participants desired for the sample. 

  II. Non random/ Non probability Sampling Researchers cannot always select random samples and must rely on non-random selection procedures. When non random sampling techniques are used, it is not possible to specify what probability each member of a population has of being selected for the sample; and it is often difficult to even describe the population from which a sample was drawn and to whom results can be generalized. Non random sampling techniques involve the following three types:

 •Convenience Sampling involves using as the sample whoever happens to be available. 

 •Purposive Sampling involves selecting a sample the researcher believes to be representative of a given population. Here, the researcher’s insights guide the selection of participants. 

 •A variety of purposive sampling techniques are used in qualitative research, including homogeneous sampling, criterion sampling, snow ball sampling, and random purposive sampling.

 •Quota Sampling involves giving interviewers exact numbers, or quotas, of persons of varying characteristics who are to be interviewed. 

 Sample Size Samples should be as large as possible. In general, the larger the sample size, the more representative it is likely to be, and the more generalizable the results of the study will be. There are no universally accepted minimum sample sizes. Minimum, acceptable sample sizes depend on the type of research, the time frame, and other resources available to the researcher.