Analyzes the difference between an observed process proportion (defectives) and a specified value.
|When to Use||Purpose|
|Pre-project||Verify the process is producing output significantly different from expectations (in this case, that usually means a higher-than-expected defect rate), which validates the need for an improvement project.|
|Mid-project||Test whether the proportion defective changed significantly when an input is controlled at a new setting or a previously uncontrolled setting is now controlled.|
|Mid-project||Verify changes from the pre-project standard, throughout the course of making improvements.|
|End of project||Verify the proportion defective from the controlled improved process is different from the pre-project proportion defective. Of course, this step assumes one of the goals of the project was to reduce the proportion defective.|
Discrete Y at exactly two levels (also called binary or binomial data). You can enter the raw data into a single column in Minitab where each row represents one observation. Or, you can enter summarized data (the number of items sampled and the number of defectives observed) in the 1 Proportion dialog box.