Food spoilage data

A food scientist wants to increase the shelf life of fruit at their stores. You can use this data to demonstrate Analyze Binary Response for Factorial Design.

A food scientist analyzes a 2-level factorial design to determine how preservative type, vacuum packaging pressure, contamination level, and cooling temperature affect the spoilage of fruit. The response is binary-whether spoilage is detected or not-in a sample of 500 containers of fruit.

You can use this data to demonstrate Analyze Binary Response for Factorial Design.

Worksheet column	Description
StdOrder	The order of the runs in standard order (also called Yates order).
RunOrder	The order of the runs in random order.
CenterPt	The center points. This design has no center points.
Blocks	The blocks. In this design, all the design points are contained in a single block.
Preservative	The food preservative: Formula 1 or Formula 2.
VacuumPress	The vacuum sealing pressure: 5 or 25.
ContaminationLevel	The initial contamination level: 5 or 50.
CoolTemp	The storage cooling temperature: 10 or 20.
Spoilage	The number of containers of fruit that have spoilage as detected by electronic sensor.
Containers	The number of fruit containers that are sampled.

Download FoodSpoilage.MWX