| sampling method | definition | application |
|---|---|---|
| Random Sampling | Each member from a population has an even chance of being picked | Best used when you have a smaller dataset. |
| Simple Random Sampling | Each sample from a population has an even chance of being picked | Larger population and you can make sure samples have an even chance of being picked. |
| Systematic Sampling | Choose some starting point then select every kth element in the population. | If the data is random and there is no pattern. |
| Convenience Sampling | Easiest way to get data. | - |
| Stratified Sampling | Divide data into two groups and select samples from each subgroup. | When you can divide your data into mutually exclusive subgroups you can take samples from. |
| Cluster Sampling | Divide population into clusters and randomly select some clusters (and all people from those clusters). | Best for large, spread out populations and/or populations that naturally form into clusters. |
| Voluntary response sample | Subjects decide themselves whether to be included in the sample. | When only the sample group that is more inclined to respond matters. |
addition rule
Note - If A and B are Independent $P(A\cap B)=0$
multiplication rule
Note - If A and B are independent $P(B|A)=P(B)$
requirements probability distribution
parameters for a frequency distribution