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Data Collection & Analysis Methods Flashcards

7 cards from real CQIA 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 & Analysis Methods flashcards as text
  1. Which tool would BEST help a team identify which single defect category to address first to achieve the greatest quality improvement?

    Answer: Pareto chart

    A Pareto chart ranks defect categories by frequency, visually identifying the vital few that cause the majority of problems.

  2. What is the primary purpose of a control chart's upper and lower control limits?

    Answer: To distinguish common cause from special cause variation

    Control limits define the expected range of process variation; points outside them signal special causes requiring investigation.

  3. A quality engineer plots defect counts against production speed and finds r = 0.92. What does this suggest?

    Answer: Strong positive correlation between speed and defects

    A correlation coefficient of 0.92 indicates a strong positive relationship, suggesting defects increase as speed increases.

  4. Which data type is BEST analyzed using a p-chart?

    Answer: Proportion of defective items in a sample

    A p-chart monitors the proportion (fraction) of nonconforming items in subgroups of varying or constant size.

  5. In the context of data collection, what is operational definition MOST important for?

    Answer: Ensuring consistent measurement and interpretation

    An operational definition specifies exactly what and how to measure so all collectors interpret the criteria the same way.

  6. A team reviews a fishbone diagram and identifies five potential root causes. What is the NEXT logical step?

    Answer: Collect data to verify which causes are actually contributing

    After identifying potential causes via a fishbone, data should be collected to confirm which causes are truly driving the problem.

  7. Which measure of central tendency is MOST resistant to the effect of extreme outliers?

    Answer: Median

    The median is the middle value in ordered data and is not distorted by extreme high or low values the way the mean is.