Because the recursive formula needs a previous forecast, the video demonstrates a simple initialization method: set the first forecast equal to the first actual observation. In the example this gives F(1)=A(1)=1103.
Conditions: Applies when no earlier forecast is available.; Shown specifically for Week 1 in the example.
Because the recursive formula needs a previous forecast, the video demonstrates a simple initialization method: set the first forecast equal to the first actual observation. In the example this gives F(1)=A(1)=1103.
Conditions: Applies when no earlier forecast is available.; Shown specifically for Week 1 in the example.
Within this clip, the setup is completed through the Week 2 formula and the recursion pattern for later weeks is explained; the numerical Week 11 forecast is not yet computed on screen.
Conditions: The clip ends after demonstrating the Week 2 formula entry.; The goal stated at the beginning is to find the Week 11 forecast.
Within this clip, the setup is completed through the Week 2 formula and the recursion pattern for later weeks is explained; the numerical Week 11 forecast is not yet computed on screen.
Conditions: The clip ends after demonstrating the Week 2 formula entry.; The goal stated at the beginning is to find the Week 11 forecast.
Alpha is defined in the video as the exponential smoothing constant. It multiplies the previous forecast error and determines the size of the adjustment added to the previous forecast.
Conditions: Treated as a given constant in the problem.; Held fixed across all periods in the example.
Alpha is defined in the video as the exponential smoothing constant. It multiplies the previous forecast error and determines the size of the adjustment added to the previous forecast.
Conditions: Treated as a given constant in the problem.; Held fixed across all periods in the example.
The video presents the single-parameter exponential smoothing update rule. The new forecast equals the prior forecast plus a fraction alpha of the prior forecast error, where the error is measured as actual minus forecast from the previous period.
Conditions: Used recursively over discrete time periods.; Requires a starting forecast value.; In the example, alpha is supplied as 0.2.
The video presents the single-parameter exponential smoothing update rule. The new forecast equals the prior forecast plus a fraction alpha of the prior forecast error, where the error is measured as actual minus forecast from the previous period.
Conditions: Used recursively over discrete time periods.; Requires a starting forecast value.; In the example, alpha is supplied as 0.2.
The video translates the mathematical recurrence into an Excel formula. For Week 2, the current forecast is computed from the Week 1 forecast in C4, the Week 1 actual in B4, and the smoothing constant in B2.
Conditions: Requires a table with actuals in one column and forecasts in another.; Uses relative references for prior row values and an absolute reference for alpha.
The video translates the mathematical recurrence into an Excel formula. For Week 2, the current forecast is computed from the Week 1 forecast in C4, the Week 1 actual in B4, and the smoothing constant in B2.
Conditions: Requires a table with actuals in one column and forecasts in another.; Uses relative references for prior row values and an absolute reference for alpha.