Quantitative Analysis for Management, 13/e

Key Equations

(5-1)

$$\text{MAD}=\frac{\sum \left|\text{Forecast error}\right|}{n}$$

A measure of overall forecast error called mean absolute deviation.

(5-2)

$$\text{MSE}=\frac{\sum {\left(\text{Error}\right)}^2}{n}$$

A measure of forecast accuracy called mean squared error.

(5-3)

$$\text{MAPE}=\frac{\sum \left|\frac{\text{Error}}{\text{Actual}}\right|}{n}100\%$$

A measure of forecast accuracy called mean absolute percent error.

(5-4)

$$\begin{array}{l}\text{Moving }\\ \text{average}\text{=}\frac{\text{Sum of demands in previous }n\text{ periods}}{n}\\ \text{forecast}\end{array}$$

An equation for computing a moving average forecast.

(5-5)

$$F_{t+1}=\frac{Y_t+Y_{t-1}+\cdots +Y_{t-n+1}}{n}$$

A mathematical expression for a moving average forecast.

(5-6)

$$F_{t+1}=\frac{\sum \left(\text{Weight in period }i\right)\left(\text{Actual value in period }i\right)}{\sum \left(\text{Weights}\right)}$$

An equation for computing a weighted moving average forecast.

(5-7)

$$F_{t+1}=\frac{w_1{Y}_t+w_2{Y}_{t-1}+\cdots +w_n{Y}_{t-n+1}}{w_1+w_2+\cdots +w_n}$$

A mathematical expression for a weighted moving average forecast.

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