*2.8. Logistical Regression*

Using prior observations from a dataset, a statistical analysis technique called logistic regression predicts a binary outcome, such as yes or no. Using a logistic regression model, a dependent data variable is predicted by looking at the correlation between the independent variables that are already present. For instance, logistic regression may be used to foretell a candidate's outcome in a political election or whether a high school student will be accepted into a particular college. These simple choices between two options allow for binary outcomes. Thirty input variables were gathered from the patient records, including clinical information (gender, age, body mass index, and concurrent disorders), laboratory testing, and histopathologic results of the gallbladder. The identical database was used to produce a logistic regression model, and similar data were compared to the outcome [34].
