10
Feb
Define Stratified Random Sample. Stratified random sampling is applied to obtain a sample from multiple strata to increase the generalizability of the research. The proportion of such sample is to be collected from each stratum and it is determined before starting the process of sampling. In a stratified random sample design the units in the sampling frame are first divided into groups called strata and a separate SRS is taken in each stratum to form the total sample. It is theoretically possible albeit unlikely that this would not happen when using other sampling methods such as simple random sampling.
In a stratified random sample design the units in the sampling frame are first divided into groups called strata and a separate SRS is taken in each stratum to form the total sample. Define the target population. Stratified sampling also known as stratified random sampling or proportional random sampling is a method of sampling that requires that all samples need to be grouped in accordance to some parameters and choosing samples from each such group instead of taking randomly from the entire population. The counterpart of this sampling is Non-probability sampling or Non-random sampling. Researchers often take samples from a population and use the data from the sample to draw conclusions about the population as a whole. The stratification variables should relate to the purposes of the study.
Researchers often take samples from a population and use the data from the sample to draw conclusions about the population as a whole.
Identify stratification variables and determine the number of strata to be used. A stratified random sample allows to first divide the population into different strata representing different caste then the sample is drawn from each stratum to study the research and study the whole population. One commonly used sampling method is stratified random sampling in which a population is split into groups and a certain number of members from each group are randomly selected to be included in the sample. Stratification is often used in complex sample designs. The counterpart of this sampling is Non-probability sampling or Non-random sampling. Researchers often take samples from a population and use the data from the sample to draw conclusions about the population as a whole.