Demand_Planning

How to create and evaluate forecasts?

We'll start by exploring the nature of time series data with scatter plots and moving average plots. Then we'll examine data bias and accuracy using methods including mean apps through deviation and sum of squared errors. Next we'll try out trend lines for forecasting. Then we'll model exponential growth, and compute CAGRs or compound annual growth rates. And finally, let's understand seasonality of data and how to forecast with multiple regression.

Content:

• Visually Displaying Your Time-Series Data
• How Good Are Your Forecast? Errors, Accuracy, and Bias
• Using a Trendline for Forecast
• Modeling Exponencial Growth and Compoud Annual Growth Rate (CAGR)
• Seasonality and the Ratio-to-Moving-Average Method
• Forecasting with Multiple Regressions