Data collection
Data collection is a process of collecting and measuring information on variables of interest, that enables the researcher to test hypotheses and evaluate outcomes.
Data can be collected with a sample or with a controlled experiment:
A sample is a small group that is selected from a large population by using a pre- defined sampling method. The sample must be representative and random.
A controlled experiment is an experiment made on an experimental group, while one factor that is being tested is changed by the researchers and all other factors are held constant.
Each controlled experiment must have a control group. In the control group we don’t change the factor that is being tested in the experimental group. The participants of the control group must be randomly selected and must closely resemble the participants in the experimental group.
Data inference
Data inference is a generalization about a population that is based on statistics calculated from a small group (a sample) that is drawn from that population.
An estimate is a process of finding a value of a population that is close enough to the right value, by performing a sample on a part of that population.
A sample proportion is a variable that is calculated from the sample, that we assume reflects the whole population.
The estimate formula: estimate= sample proportion * population
A margin of error is the degree of error in results received from random sampling surveys, it exists since the sample does not exactly match the population.
The range formula: range= estimate ± margin of error
Continue reading this page for detailed explanations and examples.