1. What is Forecast Variance?

Forecast variance is a statistical measure that quantifies the average squared difference between actual values and forecasted values. It provides insight into the accuracy and reliability of forecasting models.

2. How Does the Calculator Work?

The calculator uses the forecast variance formula:

Where:

• \( \text{Actual}_i \) — The actual observed value
• \( \text{Forecast}_i \) — The predicted or forecasted value
• \( n \) — The number of observations

Explanation: The formula calculates the average of the squared differences between actual and forecasted values, providing a measure of forecast accuracy.

3. Importance of Forecast Variance

Details: Forecast variance is crucial for evaluating the performance of forecasting models, identifying areas for improvement, and making informed decisions based on forecast reliability.

4. Using the Calculator

Tips: Enter actual and forecast values as comma-separated lists. Both lists must contain the same number of numeric values.

5. Frequently Asked Questions (FAQ)

Q1: What does a high forecast variance indicate?
A: A high variance indicates poor forecast accuracy with large differences between actual and predicted values.

Q2: How is forecast variance different from MSE?
A: Forecast variance is essentially the same as Mean Squared Error (MSE) for forecasting applications.

Q3: What are typical variance values?
A: There's no universal "good" value - it depends on the scale of your data and the context of your forecasting problem.

Q4: Can I use this for time series forecasting?
A: Yes, forecast variance is commonly used to evaluate time series forecasting models.

Q5: Should I use variance or standard deviation?
A: Variance is in squared units, while standard deviation (square root of variance) is in the original units. Both are useful depending on your analysis needs.