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Discover advanced techniques for improving forecast accuracy by analyzing patterns, identifying biases, and refining predictions. Businesses can then refine their models to avoid recurring inaccurate biases. Graphing Forecasts vs. Actuals: Use scatterplots to identify patterns of bias, such as overoptimism or sandbagging, by comparing forecasted amounts to actual results. Overoptimism and Sandbagging: Graphs can reveal consistent overestimation (overoptimism) or underestimation (sandbagging) in forecasts, helping to adjust future predictions. Variance Statistical Calculations: Metrics like Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Weighted Average Percentage Error (WAPE) quantify forecast accuracy and expose offsetting errors. Adjusting Forecasts for Bias: Use past variance statistics to adjust future forecasts, either by applying weighted adjustments (WAPE) or regression-based corrections for slope and intercept. This video comes from my Improving Financial Forecast Accuracy course at https://cfoperspective.com/improving-... CPAs: Want to get CPE credit for videos like this? Check out my CPE page at https://cfoperspective.com/cpe/