Business Analytics: Forecasting with Trended Baseline Smoothing
With Conrad Carlberg
Liked by 807 users
Duration: 1h 1m
Skill level: Advanced
Released: 10/5/2018
Course details
Simple exponential smoothing (SES) incorporates most of the elements used in the smoothing approach to forecasting, such as a level smoothing constant, self-correction, and the gradual weakening of the influence of older observations on new forecasts. But SES works poorly with baselines that display either trends or seasonality. The trended time series is one step up in complexity from the stationary time series analyzed by SES—its baseline trends up or down. The use of exponential smoothing with a trended baseline is often called Holt's method, and this course was designed to equip you with this technique. Here, instructor Conrad Carlberg explains how to use Holt's method to create forecasts in R that deal with trends in a baseline.
Skills you’ll gain
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Meet the instructor
Learner reviews
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Rupali Sharma
Rupali Sharma
Transaction Monitoring, Ongoing due diligence, Customer Due diligence, Screening and Banking Operations
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Malika Bhateja
Malika Bhateja
Associate at Nokia
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Shawna Caudill MSN, RN, CCS
Shawna Caudill MSN, RN, CCS
Senior Quality Assurance Clinical Professional
Contents
What’s included
- Practice while you learn 1 exercise file
- Learn on the go Access on tablet and phone
- Stay up to date Continuing Education Units