Lecture 2 - Forecasting Why forecast? Features Common to...

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Unformatted text preview: Forecasting Why forecast? Features Common to all Forecasts Conditions in the past will continue in the future Rarely perfect Forecasts for groups tend to be more accurate than forecasts for individuals Forecast accuracy declines as time horizon increases Elements of a Good Forecast Timely Accurate Reliable (should work consistently) Forecast expressed in meaningful units Communicated in writing Simple to understand and use Steps in Forecasting Process Determine purpose of the forecast Establish a time horizon Select forecasting technique Gather and analyze the appropriate data Prepare the forecast Monitor the forecast Types of Forecasts Qualitative o Judgment and opinion o Sales force o Consumer surveys o Delphi technique Quantitative o Regression and Correlation (associative) o Time series Forecasts Based on Time Series Data What is Time Series? Components (behavior) of Time Series data o Trend o Cycle o Seasonal o Irregular o Random variations Nave Methods Nave Forecast uses a single previous value of a time series as the basis of a forecast. Techniques for Averaging What is the purpose of averaging? Common Averaging Techniques o Moving Averages o Exponential smoothing Moving Average Exponential Smoothing Techniques for Trend Linear Trend Equation Curvilinear Trend Equation Techniques for Seasonality What is seasonality?...
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Lecture 2 - Forecasting Why forecast? Features Common to...

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