Comparing Forecasting Methods in Excel: MAD, MSE, and MAPE - BrandonPhD

*Please note that in this video I use sales instead of demand. Demand is the more appropriate term for what I am using as sales and demand do vary.* (I asked ChatGPT to write a video description based on the title of this video... haha!) Welcome to our video on comparing forecasting methods! In this video, we delve into the world of forecasting and explore the calculation of three important metrics: MAD (Mean Absolute Deviation), MSE (Mean Squared Error), and MAPE (Mean Absolute Percentage Error). We compare the performance of three popular forecasting techniques: Naive, Simple Moving Average (SMA), and Weighted Moving Average (WMA). By analyzing these methods, we aim to provide valuable insights into their strengths, weaknesses, and overall accuracy in predicting future trends. Throughout the video, we break down the calculation process of MAD, MSE, and MAPE, showcasing how these metrics can be utilized to evaluate forecast quality and measure the degree of accuracy. Whether you're new to forecasting or looking to enhance your understanding of these methods, this video is packed with informative content. Join us as we explore the intricacies of time series forecasting, dive into data analysis, and discuss statistical forecasting techniques. By the end of this video, you'll have a solid grasp of the importance of forecast evaluation and the practical application of different forecasting approaches. If you're interested in honing your forecasting skills or seeking to improve your business forecasts, this video is a must-watch. Don't miss out on the opportunity to gain valuable insights and enhance your forecasting expertise. Hit the play button now and embark on this educational journey with us. Remember to like, share, and subscribe to our channel for more informative videos on data analysis, predictive modeling, and business forecasting. Let's uncover the secrets behind accurate predictions together!