Which forecasting approach uses mathematical models and historical data to make forecasts?

Which forecasting approach uses mathematical models and historical data to make forecasts?

• A. Qualitative forecasting
• B. Quantitative forecasting
• C. Customer survey
• D. Time Series

Answer: (B)

Quantitative forecasting relies on numerical data and mathematical models to predict future demand. It uses historical data to uncover patterns—such as trends, seasonality, and cycles—and then applies statistical techniques to project those patterns forward. This data-driven, model-based approach is capable of back-testing and validating accuracy, making it a reliable choice when past values and mathematical relationships guide the forecast. Qualitative forecasting, on the other hand, depends on expert judgment and opinions rather than numerical models. A customer survey provides information, but it isn’t itself a forecasting method. Time series is a common quantitative technique that analyzes historical data over time, but it’s a specific method within quantitative forecasting; the broader approach that centers on math and data is quantitative forecasting.

Quantitative forecasting relies on numerical data and mathematical models to predict future demand. It uses historical data to uncover patterns—such as trends, seasonality, and cycles—and then applies statistical techniques to project those patterns forward. This data-driven, model-based approach is capable of back-testing and validating accuracy, making it a reliable choice when past values and mathematical relationships guide the forecast. Qualitative forecasting, on the other hand, depends on expert judgment and opinions rather than numerical models. A customer survey provides information, but it isn’t itself a forecasting method. Time series is a common quantitative technique that analyzes historical data over time, but it’s a specific method within quantitative forecasting; the broader approach that centers on math and data is quantitative forecasting.