Complete \"Example 13.2: Process Control Chart Design,\" located in Chapter 13 o

Question

Complete "Example 13.2: Process Control Chart Design," located in Chapter 13 of the textbook. Write a 150-300-word paragraph comparing the simple moving average weighted moving average, exponential smoothing, and linear regression analysis time series models. Complete "Example 18.4: Computing Trend and Seasonal Factor From a Linear Regression Line Obtained With Excel," located in Chapter 18 of the textbook. Write a 150-300-word paragraph explaining the market research, panel consensus, historical analogy, and Delphi method qualitative forecasting techniques. Prepare your responses in Excel with each problem on a separate tab.

Explanation / Answer

Simple Moving Average: This method uses several demand values during the recent past to develop a forecast. This tends to dampen or smooth out the random increase and decreases of a forecast that uses only one period.This simple moving average is useful for demand that is stable and does not display any pronounced demand behavior such as trend and seasonal pattern.

Weighted moving Average: This method can be adjusted to more closely reflect fluctuations in the data. In the weighted moving average method, weighs are assigned to the most recent data. Determining the precise weights for each period of data usually requires trial and error experimentation as does determining the no. of periods to include in the moving average.

Exponential Smoothing: It is also an averaging method that weighs the most recent data more strongly. As such, the forecast will react to recent changes in demand. This is useful if the recent changes in the data are significant and unpredictable instead of just random fluctuations.

Linear Regression analysis: It is mathematical technique that relates one variable called as independent variable to another dependent variable in the form of an equation for a straight line. Linear regression is used as a forecasting model for demand, the dependent variable, y, represent demand and x is an independent variable that causes demand to behave in a linear manner.

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