Binary Logistic Regression for Predict Damage-free Delivery

Use Binary Logistic Regression to use multiple predictors to predict damage-free delivery.

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

Example

Damage-free delivery is the proportion of orders that are delivered without damage.

In this worksheet, Damage is the response. The response event is Undamaged. Number of Items is a continuous predictor, and Case Size is a categorical predictor.

C1-T	C2	C3-T
`Damage`	`Number of Items`	`Case Size`
Damaged	5	6-bottle
Damaged	4	4-bottle
Undamaged	2	2-bottle
Undamaged	1	1-bottle

How-to

Choose Solutions Modules > Functions > Supply Chain KPIs, then select Launch.
Under Quality, select Damage-free delivery.
Select Predict damage-free delivery, then click OK.
Select Binary Logistic Regression, then click OK.
In Response, enter the binary variable that contains the damage data. Binary variables are categorical variables that have two possible levels, such as pass/fail or true/false. The response is also called the Y variable.
In Response event, select the value that represents an undamaged delivery.
(Optional) In Frequency, enter the column that contains the counts that correspond to the response and predictor values in the row.
In Continuous predictors, enter the continuous variables that may explain or predict whether a delivery is damaged. The predictors are also called X variables.
In Categorical predictors, enter the categorical variables that may explain or predict whether a delivery is damaged. The predictors are also called X variables.
Click OK.

Tip

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