1. What is Discriminant Analysis?

Discriminant analysis is a statistical technique used to classify observations into distinct groups based on predictor variables. It creates a discriminant function that maximizes separation between groups.

2. How Does the Calculator Work?

The calculator uses the discriminant function:

Where:

• \( D \) — Discriminant score
• \( b_0 \) — Constant term
• \( b_1, b_2, \ldots, b_n \) — Coefficients for each variable
• \( X_1, X_2, \ldots, X_n \) — Predictor variables

Explanation: Observations are classified based on whether their discriminant score is above or below the cutoff value (typically 0).

3. Importance of Discriminant Function

Details: Discriminant analysis is widely used in medical diagnosis, marketing research, and social sciences for classification problems with well-defined groups.

4. Using the Calculator

Tips: Enter values for your predictor variables. You can use either the default model coefficients or provide your own custom coefficients for specialized applications.

5. Frequently Asked Questions (FAQ)

Q1: What's the difference between linear and quadratic discriminant analysis?
A: Linear assumes equal covariance matrices across groups, while quadratic allows different covariance structures.

Q2: How many variables can I include?
A: The calculator supports up to 3 variables for simplicity, but real analyses often include more.

Q3: What does the discriminant score represent?
A: It's a weighted combination of predictors that best separates the groups. Higher absolute values indicate stronger classification.

Q4: How accurate is this method?
A: Accuracy depends on having good separation between groups in your data and appropriate variable selection.

Q5: Can I use this for more than two groups?
A: This calculator is for two-group classification. Multiple discriminant analysis handles more groups.