1. Random Samples Random digit table
Simple random sample (SRS): every sample of size n has the same chance of being selected

2. Random Samples
stratified random sample – Take a random selection from determined homogeneous groups.
multistage sample design – Take multiple samples with increasing precision.

3. Random Samples
systematic random sample – choose a starting number at random and then add a constant, x, to determine the next subject sampled. Continue through the entire population.
cluster random sample – divide the population in groups based on a homogeneous quality and take an SRS of each group

4. Random Samples
The fact that every individual has an equal chance of selection, by itself, is not enough to guarantee that the sample is a simple random sample.

5. Random Samples
Sample results do not necessarily match population results.
Results may change from sample to sample, but since we deliberately use chance, the results obey the laws of probability allowing fairly consistent results (within a margin of error).

6. Random Samples
The degree of accuracy can be improved by increasing the size of the sample.