What is marginal distribution?

Marginal distribution refers to the statistical distribution of a subset of data from a larger dataset. It essentially shows the frequency or probability of each value within a single variable, regardless of the values of other variables.

Marginal distributions are often used in analyzing multivariable data, such as in contingency tables or probability distributions. By extracting and examining the marginal distributions of individual variables, researchers can gain insights into the relationship between variables and identify patterns or trends within the data.

In a contingency table, marginal distributions are represented in the margins of the table, hence the name. By looking at the marginal distributions of the rows and columns separately, researchers can analyze the individual variables without considering the joint distribution of the variables.

Marginal distributions can be calculated by summing or averaging the values of one variable while ignoring the values of other variables. This allows researchers to isolate and study the behavior of individual variables within a dataset.

In summary, marginal distribution is a useful tool in statistical analysis that allows researchers to examine the frequency or probability distribution of individual variables within a larger dataset, without considering the joint distribution of all variables.