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Data Collection & Interpretation Flashcards

7 cards from real SPC practice questions. Tap to flip, then mark Knew It or Still Learning โ€” missed cards come back until you master them.

Read the first 7 Data Collection & Interpretation flashcards as text
  1. A quality engineer wants to track the number of defects per unit on an assembly line. Which type of data is this?

    Answer: Attribute data

    Count of defects per unit is attribute (discrete) data because it represents countable occurrences rather than measured values.

  2. When collecting data for SPC, a rational subgroup is best described as:

    Answer: A sample collected under the same conditions to minimize within-group variation

    A rational subgroup is formed so that variation within the subgroup is minimized and only represents common cause variation, making between-subgroup variation easier to detect.

  3. Which sampling strategy is MOST appropriate when a process has known periodic cycles or patterns?

    Answer: Systematic sampling aligned to cycles

    Systematic sampling aligned with known cycles ensures the pattern is captured rather than aliased or missed during data collection.

  4. On a check sheet used for defect collection, a tally mark represents:

    Answer: One occurrence of a specific event or defect type

    Each tally mark on a check sheet records one occurrence, enabling easy frequency counts by category.

  5. A dataset has values: 10, 12, 11, 100, 13. The value 100 is most likely a(n):

    Answer: Outlier that should be investigated before analysis

    A value far removed from the others is an outlier and should be investigated for measurement error or a special cause before using the data.

  6. The primary purpose of stratifying data during collection is to:

    Answer: Separate data into meaningful subgroups to identify hidden sources of variation

    Stratification splits data by factors like shift, machine, or operator to reveal variation sources that would be obscured in pooled data.

  7. Which measure of central tendency is LEAST affected by extreme values in a dataset?

    Answer: Median

    The median is a positional measure that is resistant to outliers, unlike the mean which is pulled toward extreme values.