Aditya Shinde

Roll no 1

Group 1

Stratified Random Sampling

1)More often than not, you will not only want to examine the results from the overall population, but also understand the differences between key demographic subgroups within the population.

2) For example, you might want to understand the differences between different groups of employees, like senior managers vs. regular employees.

3) If you plan to look at distinct subgroups such as these, you should perform a stratified random sample. In a nutshell, this means you will need to select a separate random sample from each of the subgroups rather than just taking a single random sample from the entire group.

4)The process is slightly more time consuming and will require you to survey a greater number of people overall, but this technique can be very valuable. 

5)If you want to conduct a stratified random sample, think carefully about the single most relevant demographic division that can be made between people within your population.

6) It is probably not practical to conduct a stratified random sample on more than one demographic category as the process becomes much more complex and you will ultimately end up needing to survey almost the entire population if any of the subgroups are very small.

7) For example, if you wanted to look at employee survey results and by level and job function, you would need to look at each level/function combination and you might find very small numbers of employees within some of these areas.