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Basic Statistical Tools Flashcards

7 cards from real Lean Six Sigma Green Belt Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.

Read the first 7 Basic Statistical Tools flashcards as text
  1. In hypothesis testing, what does the p-value represent?

    Answer: The probability of observing results as extreme as the sample if the null hypothesis is true

    The p-value is the probability of obtaining the observed data (or more extreme) assuming the null hypothesis is true.

  2. A Type II error in hypothesis testing occurs when you:

    Answer: Fail to reject a false null hypothesis

    A Type II error (β) means failing to detect a real effect — accepting H₀ when it is actually false.

  3. What does a Cpk value of 1.33 indicate about a process?

    Answer: The process is capable and has some margin relative to the nearest specification limit

    Cpk = 1.33 is the traditional minimum target, indicating the process mean is at least 4σ from the nearest spec limit.

  4. Which statistical test compares the means of exactly two independent groups?

    Answer: Two-sample t-test

    A two-sample t-test compares the means of two independent groups to determine if they differ significantly.

  5. What is the interquartile range (IQR) used to measure?

    Answer: The spread of the middle 50% of data

    IQR = Q3 − Q1, capturing the spread of the central 50% of the data and resisting outlier influence.

  6. A box plot whisker extends to a data point that is 1.7 × IQR above Q3. How should this point be classified?

    Answer: A normal data point within the whisker

    Box plot whiskers typically extend to 1.5 × IQR; 1.7 × IQR falls outside that but the point itself is still plotted at its actual value — it would actually be an outlier (mild) since 1.7 > 1.5.

  7. Which type of variation in a process is attributable to identifiable, non-random causes?

    Answer: Special cause variation

    Special cause variation is assignable to specific, identifiable factors and is not part of the normal process distribution.