Compute the one-step-ahead 3-month and 6-month moving-average forecasts for July through December. b. Compute the MAD for the forecasts obtained in part (a). What effect does increasing N from 3 to 6 have on the forecasts? c. Use the arithme
Continuous Probability Distributions
Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could count from 0 to a trillion seconds, billion seconds, so on indefinitely. A discrete probability distribution consists of only a countable set of possible values.
Normal Distribution
Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a great idea as the sensitivity of the scale would get reduced if the range is too large. At the same time, if we keep the upper limit too low, it may not be usable for a large percentage of the population!
|
Month |
Jan |
Feb |
Mar |
Apr |
May |
Jun |
Jul |
Aug |
Sep |
Oct |
Nov |
Dec |
|
Sales |
238 |
220 |
195 |
245 |
345 |
380 |
270 |
220 |
280 |
120 |
110 |
85 |
a. Compute the one-step-ahead 3-month and 6-month moving-average forecasts for July through December.
b. Compute the MAD for the forecasts obtained in part (a). What effect does increasing N from 3 to 6 have on the forecasts?
c. Use the arithmetic average of the first six months of data as a baseline to initialize the exponential smoothing. Compute the one-step-ahead exponential smoothing forecasts for July through December,
assuming α = 0.20.
Given information:
The data presents the sample for the months January through December.
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