What is exponential regression?

Exponential regression fits a curve of form y = ab^x or y = ae^(kx) to data points. It models growth/decay processes where change is proportional to current value.

When should I use exponential vs linear regression?

Use exponential when data shows percentage-based growth (doubling, halving) or multiplicative patterns. Use linear when change is constant (adding fixed amount).

What is the R² value?

R² (coefficient of determination) measures how well the model fits data. Values range 0-1; closer to 1 means better fit. Above 0.9 is typically excellent.

How do I calculate doubling time?

For y = ab^x: doubling time = ln(2)/ln(b). For y = ae^(kx): doubling time = ln(2)/k. Half-life uses the same formulas for decay.

What is the growth rate?

For y = ab^x: growth rate = (b-1)×100%. For y = ae^(kx): k is the continuous growth rate. Positive = growth, negative = decay.

Exponential Regression Calculator

Fit an exponential model (y = a·b^x) to your data with step-by-step calculations

Data Input

Enter Data Points (x, y per line)

Note: y values must be positive for exponential regression

Load Example:

Results

Enter data points and click calculate to see the exponential regression

About Exponential Regression

The Exponential Model

y = a · b^x

a: Initial value (y-intercept when x = 0)
b: Growth/decay factor per unit x
b > 1: Exponential growth
0 < b < 1: Exponential decay

Applications

• Population growth modeling
• Radioactive decay
• Compound interest
• Bacterial growth
• Drug concentration decay
• Moore's Law (technology)

Related Calculators

Hypothesis Testing Normal CDF Frequency Distribution Compound Interest

About Exponential Regression Calculator - Curve Fitting

Fit exponential models (y = ab^x) to your data points using regression analysis. Calculate growth rates and predict future values.

Our **Exponential Regression Calculator** fits exponential curves to your data using least squares regression. Enter x,y data pairs to find the best-fit equation y = ab^x or y = ae^(kx). For linear models, see our Linear Programming Calculator.

Exponential regression is ideal for modeling growth phenomena like population, compound interest, radioactive decay, and viral spread. The calculator provides correlation coefficient (r²) to assess fit quality.

Beyond finding the equation, use this tool to predict future values, calculate doubling time or half-life, and compare with linear models to determine which fits your data better.

Key Features

Exponential curve fitting

Multiple model forms (ab^x, ae^kx)

Correlation coefficient R²

Growth/decay rate calculation

Value prediction

Doubling time/half-life

Why Use This Tool?

Model growth patterns

Make accurate predictions

Quantify growth rates

Compare model fits

Understand data trends

Common Use Cases

Biology: Population growth modeling.

Finance: Investment growth projections.

Physics: Radioactive decay analysis.

Epidemiology: Disease spread prediction.

Related Tools

Compound Interest Calculator

Financial growth calculations.

Log Calculator

Logarithmic calculations.

How to Use

Enter your x,y data pairs

Select model form

Click Calculate

View equation and R² value

Use for predictions