Docs/content/python/concepts/statsmodels/terms/logit/logit.md

logit.md

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+---
+Title: 'Logit'
+Description: 'Returns the log-odds of a binary outcome using logistic regression.'
+Subjects:
+  - 'Python'
+  - 'Statistics'
+Tags:
+  - 'logit'
+  - 'logistic-regression'
+  - 'statsmodels'
+CatalogContent:
+  - 'learn-statistics'
+  - 'path/python-data-science'
+---
+
+## Introduction
+
+**Logit** is a term used in statistics, specifically in the context of logistic regression. It represents the log-odds of a binary outcome, mapping probabilities from the 0 to 1 range to the entire real number line. The **logit** function is a key part of many statistical models, particularly in binary classification tasks.
+
+## Syntax
+
+```python
+statsmodels.api.Logit(endog, exog)
+
+endog: The dependent (binary) variable, which must be a binary outcome (0 or 1).
+exog: The independent variables (features or predictors).
+
+Example
+This example demonstrates how to use the Logit function in the statsmodels library to perform logistic regression.
+Python:
+import statsmodels.api as sm
+
+# Example data
+X = sm.add_constant([[1], [2], [3], [4], [5]])  # Adding a constant for the intercept
+y = [0, 0, 1, 1, 1]
+
+# Fitting the logistic regression model
+model = sm.Logit(y, X)
+result = model.fit()
+
+# Output the results
+print(result.summary())
+
+Note: The dependent variable (y) must contain only binary values (0 or 1) for logistic regression to be valid.
+
+Output
+This example produces a summary of the logistic regression model's results, showing coefficients, standard errors, p-values, and other statistics relevant to evaluating the model fit.
+
+Codebyte Example:
+import statsmodels.api as sm
+
+# Example data
+X = sm.add_constant([[1], [2], [3], [4], [5]])  # Adding a constant for the intercept
+y = [0, 0, 1, 1, 1]
+
+# Fitting the logistic regression model
+model = sm.Logit(y, X)
+result = model.fit()
+
+# Output the results
+result.summary()
+This code performs the logistic regression and outputs the summary directly in an interactive code environment.