# iii. Predictive Modeling & Forecasting

Predictive modeling and forecasting use historical and real-time data to estimate future outcomes. These techniques support planning, risk assessment, and decision-making by providing probabilistic views of what may occur under defined assumptions.

#### **Baseline Forecast**

An initial projection based on current conditions and standard assumptions.

#### **Confidence Interval**

A range of values that expresses the uncertainty associated with a prediction.

#### **Forecast Horizon**

The length of time into the future for which predictions are generated.

#### **Input Variable**

A data element used by a predictive model to generate outputs.

#### **Model Assumption**

A condition or premise built into a predictive model that shapes its results.

#### **Predictive Model**

A model designed to estimate future outcomes based on historical patterns.

#### **Regression Analysis**

A statistical method used to estimate relationships between variables.

#### **Scenario Analysis**

The evaluation of multiple possible future outcomes based on different assumptions.

#### **Time Series Data**

Sequential data points collected over time, often used for forecasting trends.

#### **Forecast Error**

The difference between predicted values and actual observed outcomes.


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