Probability Sampling and its Types - Biochemistry

 

Probability Sampling and its Types - Biochemistry  Probability Sampling and its Types - Biochemistry  Definition:   If every unit of the sample has some equal chance of selection, then it is called probability sampling design. OR Probability Sampling and its Types - Biochemistry It is a sampling design in which units are selected randomly, using a probability approach. When data is random or generalized its result can be generalized to the population. These plans or designs are mathematically proven. The reliability of the probability sampling designs is very high. Types of Probability Sampling There are different types of probability sampling. Some of the most common types are mentioned below: Simple random sampling Stratified sampling Cluster sampling Systematic random sampling Simple Random Sampling A simple random sampling design is one in which each unit has an equal chance of selection. It works when the population is homogenous i.e. all units are from the same background. If the population is heterogeneous, then simple random sampling will be misleading. If variation of data is high then a large sample size will be required but if data has low variation then a small sample size will be used for analysis. If the budget is low, a big sample size will not be feasible. To overcome this problem, an available sampling frame i.e. list of information about samples is used. Random numbers are assigned to each unit. For selecting sample units, random number tables can be used. This way all units have an equal chance of selection. Stratified Sampling This design is used when the population is heterogeneous, to convert it into a homogeneous population. A heterogeneous population is divided into different groups based on a specific factor that affects the variable. These homogeneous groups are called strata. The process is known as stratification. The proportional allocation is done for sample selection. Single stratum has homogeneity within but different strata have heterogeneity between them. nh = Nh / N ×n nh = sample size of one stratum Nh = population in one stratum N = total population n = total sample size h = 1, 2, 3… (Group number) Cluster Sampling Cluster sampling is done when the list of populations or sampling frame is not available. Also, the total size of the population is not known. It divides the population into different groups on a geographical basis. Then all experimental units are studied. Another most important feature is that there is no homogeneity or high variation within a cluster but homogeneity is observed between different clusters. Clusters are selected by random number assigning and random number table. All units are studied from a selected cluster. Systematic Random Sampling In systematic random sampling, samples are selected based on sampling interval. A sampling interval is a specific distance between a random starting point and a fixed periodic interval. The sampling interval can be determined by dividing the population size by sample size. It is a quicker process than other designs. Another point that must be taken into view is how the population list is arranged for the selection of samples. Types of Non-probability Sampling There are four important techniques of non-probability sampling Purposive Sampling Convenience Sampling Quota Sampling Snowball Sampling Purposive Sampling This is the technique in which the researcher tries to fulfill his purpose by using any method. It depends on the need of the researcher and which kind of data is required by him and he tries to get the data using any methodology that is suitable for his research. For example, the researcher wants to check the prevalence of cancer in a particular area and he takes females only as a target population. Convenience Sampling This is the technique in which convenience or ease is preferred. The researcher adopts only those methods that are easily assessable and can be handled easily. For example, if a researcher wants the data of 100 people and wants to check the percentage of Hepatitis C disease in that particular area. He will select the people who are close to its vicinity because they are easy to approach. Quota Sampling This is the kind of non-probability sampling in which there are fixed units from particular populations concerning various traits. For example, in the National Assembly of Pakistan people are selected on an electoral basis but in the Senate seats are filled according to a quota system and distributed equally among all the provinces. All provinces have equal representation. Snowball Sampling This technique of non-probability sampling is rarely used. In this technique, the first sample is selected randomly and then further information is drawn from it, and then so on. For example, if  an investigation agency is looking for a person and they are unable to find him, they will try to approach a person who has links with him and get information, and then further investigation is done. #Probability #Sampling #Biochemistry

Probability Sampling and its Types - Biochemistry