Use this data science tool to evaluate period-by-period growth, compounding behavior, forecast scenarios, and volatility from any ordered numeric series.
Calculator Inputs
Plotly Graph
Example Data Table
This sample uses monthly active users to demonstrate sequential growth analysis in a data science workflow.
| From | To | Previous Value | Current Value | Absolute Change | Growth Rate | Index Base 100 |
|---|---|---|---|---|---|---|
| Jan | Feb | 1,200.00 | 1,290.00 | 90.00 | 7.50% | 107.50 |
| Feb | Mar | 1,290.00 | 1,385.00 | 95.00 | 7.36% | 115.42 |
| Mar | Apr | 1,385.00 | 1,502.00 | 117.00 | 8.45% | 125.17 |
| Apr | May | 1,502.00 | 1,638.00 | 136.00 | 9.05% | 136.50 |
| May | Jun | 1,638.00 | 1,765.00 | 127.00 | 7.75% | 147.08 |
Formula Used
Period Growth Rate
Growth Rate = ((Current Value - Previous Value) / Previous Value) × 100
Arithmetic Average Growth
Arithmetic Mean = Sum of all period growth rates / Number of intervals
Geometric Average Growth
Geometric Mean = (Product of growth factors)^(1 / Number of intervals) - 1
Annualized CAGR
CAGR = (Ending Value / Starting Value)^(Periods Per Year / Intervals) - 1
Weighted Recent Mean
Weighted Mean = Sum(Growth Rate × Recency Weight) / Sum(Recency Weights)
Trimmed Mean Growth
Trimmed Mean removes the highest and lowest selected percentages before averaging the remaining growth rates.
How to Use This Calculator
- Enter a metric name, such as revenue, conversions, or active users.
- Choose a period label like day, week, month, or quarter.
- Set periods per year for correct annualized CAGR output.
- Paste ordered labels and numeric values into their fields.
- Pick a forecast method and optional forecast horizon.
- Submit the form to view summary metrics, interval details, exports, and the interactive graph.
FAQs
1. What does average growth rate mean?
It is the typical period-over-period percentage change across an ordered series. This page reports arithmetic, geometric, weighted, trimmed, and annualized versions for stronger trend analysis.
2. What is the difference between arithmetic and geometric averages?
Arithmetic averaging treats each period’s percentage change equally. Geometric averaging respects compounding and usually describes multi-period growth better when values evolve multiplicatively.
3. Why can CAGR differ from the average period growth?
CAGR annualizes the full start-to-end change using your selected periods per year. It smooths the path into one yearly rate, so it often differs from simple period averages.
4. Can I use negative values?
Arithmetic metrics can still work when previous values are not zero. Geometric mean and CAGR may return N/A when compounding assumptions break, especially with non-positive cumulative factors.
5. Why is a previous zero value not allowed?
Percentage growth divides change by the previous observation. When that prior value equals zero, the percentage rate becomes undefined, so the calculator blocks the interval.
6. What does trimmed mean do?
Trimmed mean removes a chosen share of the highest and lowest growth rates before averaging. It reduces outlier influence and can better represent central tendency in noisy series.
7. How are forecast values produced?
Forecasts extend the last actual value by repeatedly applying the selected average periodic rate. They are scenario estimates, not guaranteed outcomes, so validate them with domain knowledge.
8. Which average should data scientists choose?
Use arithmetic mean for simple summaries, geometric mean for compounding behavior, weighted mean for recent momentum, and trimmed mean when outliers distort the trend.