Example Of Stratified Random Sample. A simple random selection could easily end up with too many from the poor end and too few from the expensive end or vice versa leading to an unrepresentative sample. Final members for research are randomly chosen from the various strata which leads to cost reduction and improved response efficiency. Example of Stratified Random Sampling A research team has decided to perform a study to analyze the grade point averages or GPAs for the 21 million college students in the US. It may not howeverlead to any signicant reduction in the variance of an.
Then one or more choices are made at random from each stratum. The strata are formed to keep similar units together for example a female stratum and a male stratum. For example suppose alarge study region appears to be homogeneous that is there are no spatial patterns andis stratied based on the geographical proximity of sampling units. In stratified random sampling the population is divided into groups based on a shared characteristic. Example of Stratified Random Sampling A research team has decided to perform a study to analyze the grade point averages or GPAs for the 21 million college students in the US. Stratification is often used in complex sample designs.
A simple random selection could easily end up with too many from the poor end and too few from the expensive end or vice versa leading to an unrepresentative sample.
Final members for research are randomly chosen from the various strata which leads to cost reduction and improved response efficiency. Example of Stratified Random Sampling A research team has decided to perform a study to analyze the grade point averages or GPAs for the 21 million college students in the US. For example suppose you are trying to take a sample of 100 students to ask them whether or not they support a new parking lot at the school. Following is a classic stratified random sampling example. 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. Final members for research are randomly chosen from the various strata which leads to cost reduction and improved response efficiency.