The Great Crypto Escape's video: How To Calculate Exponential Smoothing Tutorial Statistics Time Series Forecasting Tutorial

Learn How To Calculate Exponential Smoothing in this Statistics Time Series Forecasting Tutorial In this Exponential Smoothing Forecasting Tutorial, you will learn the Forecasting Time Series method that relies only on Alpha levels and some other forecasting techniques. Exponential smoothing is a rule of thumb technique for smoothing time series data using the exponential window function. Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time. It is an easily learned and easily applied procedure for making some determination based on prior assumptions by the user, such as seasonality. Exponential smoothing is often used for analysis of time-series data. Exponential smoothing is one of many window functions commonly applied to smooth data in signal processing, acting as low-pass filters to remove high-frequency noise. This method is preceded by Poisson's use of recursive exponential window functions in convolutions from the 19th century, as well as Kolmogorov and Zurbenko's use of recursive moving averages from their studies of turbulence in the 1940s. Exponential Smoothing Forecasts are often one of the first time-series forecasts run by a company when they are attempting to extrapolate numbers for future months. Enjoy :) *********************************************************************** *********************************************************************** * If you purchase anything through a link in this video, you should assume that I have an affiliate relationship with the company providing the product or service that you purchase, and that I'll be compensated in some small way at no extra cost to you.