What is the main difference between C-chart and P-chart?

Question

BlackTom AI · Accepted Answer

When evaluating the relationship between C-charts and P-charts, you want to separate what each chart measures and what type of data it uses.
Option 1 proposes that C-chart monitors attributes while P-chart monitors variables. This is misleading because both C and P charts are used for attribute data, not variables or continuous measurements. C-chart tracks counts of defects per unit, not a continuous measurement, and P-chart tracks proportions of defective units, also an attribute-based metric.
Option 2 states: 'C-chart counts defects per unit, P-chart monitors proportion defective.' This aligns with standard quality control definitions: C-chart is used for counting defects per item or unit, and P-chart monitors the fraction defective in a sample, i.e., a proportion. The description matches the intended use of these charts.
Option 3 claims 'P-chart is for continuous data, C-chart is not.' In reality, both charts are used for attribute data, not continuous variables. P-charts and C-charts analyze pass/fail type information (defective or not) across samples, not continuous measurements, so this statement is incorrect.
Option 4 asserts 'There is no difference.' This is plainly false because C-charts and P-charts have distinct data types and purposes: counts of defects versus proportions of defectives, respectively.
In summary, the only option that correctly captures the distinct roles of these charts is the one describing C-chart as counting defects per unit and P-chart as monitoring proportion defective, while the others misstate the data type or the fundamental purpose of the charts.

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What is the main difference between C-chart and P-chart?

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