In scientific studies, data collection can fall under two broad categories

**observational study**- where data is recorded without interfering with the process under study. These can be of 3 basic types**sample survey**- provides info about a population at a particular point in time**prospective study**- describes the population at present using sample survey and proceeds to follow forward in time to record specific outcomes**retrospective study**- describes the population at present using sample survey and records specific occurrence that have already taken place

**experimental study**- where explanatory variables are actively manipulated and the effects on response variables are studied.

The various ways in which data collection experiments can be designed:

**Simple random sampling**- Selecting a group of*n*units in such a way that each sample of size*n*has the equal probability of being selected.**Stratified random sampling**- grouping the target population into strata based on a known auxiliary variable and then performing simple random sampling on each of the strata**cluster sampling**- this involves selecting groups (based on convenience of study, such as buildings or city blocks) based on simple random sampling and then surveying or measuring all units within the groups.**systematic sampling**- this involves selecting every*n*th value from a finite list as the sample. This technique is economical but can he heavily biased.

There are 2 types of variables in an experimental study - controlled variables (factors) and measured variables (response variables) which are under study

**factorial treatment**- each of the various factors (m,n,o..) affecting the phenomena are combined with one-another. The resulting combinations (m*n*o..) are studied individually**fractional factorial treatment**- as the number of factors increase, factorial treatment becomes impossible to complete. Then, only a few selected combinations are picked for the study forming a fractional factorial treatment.