Capability Analysis (Binomial)
overview     how to     example     data     see also 

Stat > Quality Control > Capability Analysis > Binomial

Use Capability Analysis (Binomial) to produce a process capability report when your data are from a binomial distribution. Binomial distributions are usually associated with recording the number of defective items out of the total number sampled.

For example, you might have a pass/fail gage that determines whether an item is defective or not. You could then record the total number of parts inspected and the number failed by the gage. Or, you could record the number of people who call in sick on a particular day and the number of people scheduled to work each day.

Use Capability Analysis (Binomial) if your data meet the following conditions:

·    each item is the result of identical conditions

·    each item can result in one or two possible outcomes (success/failure, go/no-go)

·    the probability of a success (or failure) is constant for each item

·    the outcomes of the items are independent of each other

Capability Analysis (Binomial) produces a process capability report that includes the following:

·    P chart - verifies that the process is in a state of control

·    Chart of cumulative %defective - verifies that you have collected data from enough samples to have a stable estimate of %defective

·    Histogram of %defective - displays the overall distribution of the %defectives from the samples collected

·    Defective rate plot (when subgroup size is not constant)- verifies the assumption of the binomial distribution that the %defective is not influenced by the number of items sampled

or

Binomial plot (when subgroup size is constant) - verifies that the binomial distribution is appropriate for your data by plotting the expected number of defective items against the number you actually observed

Dialog box items

Defectives: Enter a column containing the number of defectives from each sample or subgroup.

Sample Size

Constant size: If all the samples are the same size, you may enter a constant as the sample size.

Use Sizes In: Enter a column containing the number of items in each sample or subgroup.

Historical p (Optional): Enter a historical value for the proportion of defectives. This value must be between 0 and 1.

Enter a target % Defective for this process (Optional) Target: If you like, enter number for the % defective target.

<Tests>

<Options>

<Storage>