Logistic Regression Calculator

Logistic Regression

Logistic regression is used to predict binary outcomes and calculate probabilities. It's commonly used for classification problems where the dependent variable is categorical (typically 0 or 1).

How It Works

Unlike linear regression, logistic regression uses a logistic function to model the probability of a binary outcome. The logistic function (sigmoid) transforms any input to a value between 0 and 1:

p = 1 / (1 + e^(-z))

Where:

• p is the probability of the outcome being 1
• z is the linear combination of features (z = b₀ + b₁x₁ + b₂x₂ + ... + bₙxₙ)
• e is the base of natural logarithms

When to Use Logistic Regression

Use logistic regression when:

• Your outcome variable is binary (yes/no, true/false, 0/1)
• You want to predict the probability of an event occurring
• You need to understand the influence of various factors on the outcome

How to Use This Calculator

Enter your data below as comma-separated x,y pairs (one pair per line) or upload a CSV file. The y values should be binary (0 or 1). The calculator will find the best model and provide statistics about its performance.