The pie chart. A pie chart is a circle whorepresents the total of the data and to each category is assigned an area directly proportional to its frequency.
Linear correlation. Linear correlation represents the strength of association between two quantitative variables, without implying dependence or causality.
Propensity score. A propensity score estimates each participant’s probability of receiving a treatment based on their characteristics.
Multiple comparisons. Doing multiple comparisons increases the probability of type 1 error and of detecting a false positive by chance.
Management of non-normal data. When we are dealing with the management of non-normal data, we must use other strategies to make a hypotheses contrast.