Period Demand seasonal factor Mar-18 31,550 0.84 Apr-18 32,125 0.86 May-18 35,700 0.95 Jun-18 40,620 1.08 Jul-18 42,810 1.14 Aug-18 44,230 1.18 Sep-18 41,482 1.11 Oct-18 38,348 1.02 Nov-18 34,722 0.93 Dec-18 36,190 0.97 Jan-19 38,450 1.03 Feb-19 33,330 0.89 total 449,557 Average 37,463 What is the forecast demand for march 2019 using simple exponential smoothing with an alpha = 0.3 ?
Contingency Table
A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.
Binomial Distribution
Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.
| Period | Demand | seasonal factor | |
| Mar-18 | 31,550 | 0.84 | |
| Apr-18 | 32,125 | 0.86 | |
| May-18 | 35,700 | 0.95 | |
| Jun-18 | 40,620 | 1.08 | |
| Jul-18 | 42,810 | 1.14 | |
| Aug-18 | 44,230 | 1.18 | |
| Sep-18 | 41,482 | 1.11 | |
| Oct-18 | 38,348 | 1.02 | |
| Nov-18 | 34,722 | 0.93 | |
| Dec-18 | 36,190 | 0.97 | |
| Jan-19 | 38,450 | 1.03 | |
| Feb-19 | 33,330 | 0.89 | |
| total | 449,557 | ||
| Average | 37,463 |
What is the forecast demand for march 2019 using simple exponential smoothing with an alpha = 0.3 ?
The idea behind Exponential Smoothing for making forecasts consists of estimating the data value of certain period based on the previous data value as well as the previous forecast so that to attempt to correct for the deviation between the previous actual value and the prediction. The following formula is used to estimate the data value during the period
The Exponential Smoothing method of forecasting is a commonly used method to make forecasts based on a times series data set. Other common methods are the naive forecast method, the weighted moving averages, the moving averages forecast method and the linear trend forecasting method, just to mention a few.
Here we assume no trend component. Computing exponential smoothening with trend component provides for a more accurate prediction.
Step by step
Solved in 2 steps with 4 images
