Fit Regression Model for Predict Supply Chain Cost Per Unit

Use Fit Regression Model to use multiple predictors to predict supply chain cost per unit.

This example applies to the Supply Chain Module. For more information, go to www.minitab.com/supply-chain-module.

Example

Supply chain cost per unit is the total supply chain costs divided by the number of units sold.

In this worksheet, Supply Chain Cost/Unit ($) is the response. Number of Obsolete Items is a continuous predictor, and Auto Purchase Order is a categorical predictor. The predictors may explain differences in supply chain cost per unit.

C1	C2	C3-T
`Supply Chain Cost/Unit ($)`	`Number of Obsolete Items`	`Auto Purchase Order`
3.90	1500	No
2.56	675	Yes
4.70	2075	No
3.49	438	No

How-to

Choose Solutions Modules > Functions > Supply Chain KPIs, then select Launch.
Under Costs, select Supply chain cost per unit.
Select Predict supply chain cost per unit, then click OK.
Select Fit Regression Model, then click OK.
In Responses, enter the column that contains the supply chain cost per unit data. The response is also called the Y variable.
In Continuous predictors, enter the columns of numeric data that may explain or predict changes in supply chain cost. The predictors are also called X variables.
In Categorical predictors, enter the categorical classifications or group assignments that may explain or predict changes in supply chain cost. The predictors are also called X variables.
Click OK.

Tip

For more information about this analysis, click Help in the main dialog box.