Data

One of the main objectives of research and medical studies is to learn what associations or outcomes are not a product of chance. According to the study's design and the data it provides, a hypothesis can be accepted or rejected, allowing for a determination in correlation. Statistical tests are tools used by researchers to obtain information and meaning from pools of variable data. These tests come in several forms, including, for example, the chi-square and Fisher exact tests, and are chosen depending on the needs of the investigators and the characteristics of the variables being analyzed. Study results can be considered statistically significant based on calculated p-values and predetermined levels of significance (known as the α-level). Confidence intervals are another way to express the significance of a statistical result without using a p-value.

Variables represent information about something that can change. The design of the measurement scales, or of the methods for obtaining information, will determine the data gathered and the characteristics of that data. As a result, a variable can be qualitative or quantitative, and may be further classified into subgroups. Every possible way to express the value of a variable, or the range of the variable, is called a domain.