In relation to control charts, what does a C chart specifically study?

A C chart is specifically designed to monitor the number of defects in a process over time, making it a tool used in statistical quality control. It focuses on process variations by providing a visual representation of the defect count in a consistent sample size. This type of chart helps organizations understand how much variability exists in their processes, allowing them to identify trends, shifts, and outliers in defect rates.

The C chart is particularly useful because it tracks discrete data points—essentially the occurrence of defects, rather than the characteristics of a process or its inputs. It enables teams to recognize whether variations in defect occurrence are statistically significant and to assess the effectiveness of any improvements made to the process.

The other options focus on different aspects of data analysis or quality control. Data collection methods address how data is gathered but do not specifically pertain to the ongoing monitoring of defects. Qualitative responses relate to non-numeric data, which C charts do not handle since they deal with counts of defects rather than subjective responses. Causal relationships aim to establish links between different variables, a concept distinct from what C charts aim to achieve. Thus, the C chart's primary focus on monitoring process variations supports the selection.