A part of our research design is the data collection process. We often do this by sampling. Differentiate between random and nonrandom sampling methods. As part of your response define several random and nonrandom sampling techniques. Also, as part of your response, explain why random techniques are always to be preferred to nonrandom sampling methods.© BrainMass Inc. brainmass.com December 20, 2018, 4:29 am ad1c9bdddf
We normally have a large population of people. It is impossible to poll every single person in the population for several reasons. It would be too expensive, too time time consuming and too hard to analyze the data. So we would pull random people from our population to be included in our sample.
If it is completely random, each and every single person has an equal chance of being in the sample. Some techniques include:
- Simple Random Sampling: Here we would put all the names in the population in a hat for example, and randomly pull names out to be included in our sample. Every person has a 1/n (where n is the number of people in the population) of being selected to be in the sample
- Systematic sampling: This would be when the names for the population are put on a ...
The expert explains why random techniques are always to be preferred to nonrandom sampling methods. Data collection processes are examined.