Sampling
Random sampling
-
Stratified
-
Simple random sampling
-
Systematic sampling
Types of Sampling
Simple random sampling
- In simple random sampling, every sample has an equal chance of being selected.
- Use a random number generator or lottery sampling (names in a hat)
- This type of sampling is bias free and easy to implement. However it becomes unsuitable when your sample size becomes too high.
Systematic Sampling
- Systematic sampling gives an evenly spread distribution. To do this randomly, you should have a randomly generated offset. Samples are chosen at set and evenly spaced intervals.
\(\(k=\frac{population (N)}{sample(n)}\)\)
(starting at a random item between 1 and \(k\))
Stratified Sampling
- Stratified sampling is population divided into groups called strata and a simple random sample from each strata.
- The same proportion of people should be selected from each strata.
- This method has many advantages because it guarentees proportional representation.