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Certified Six Sigma Black Belt Hypothesis Testing Questions and Answers Flashcards

6 cards from real Certified Six Sigma Black Belt Exam practice questions. Tap to flip, then mark Knew It or Still Learning โ€” missed cards come back until you master them.

Read the first 6 Certified Six Sigma Black Belt Hypothesis Testing Questions and Answers flashcards as text
  1. What effect does increasing the sample size have on the power of a hypothesis test, assuming all other factors remain constant?

    Answer: Power increases

    Increasing the sample size reduces the standard error, making it easier to detect a true effect and thereby increasing statistical power.

  2. A Black Belt uses a chi-square test of independence. What type of data is this test designed to analyze?

    Answer: Categorical data in a contingency table

    The chi-square test of independence evaluates whether two categorical variables are associated by analyzing observed versus expected frequencies in a contingency table.

  3. Which non-parametric test is the appropriate alternative to the one-sample t-test when the normality assumption is violated?

    Answer: Wilcoxon signed-rank test

    The Wilcoxon signed-rank test is the non-parametric equivalent of the one-sample t-test, used when the data cannot be assumed to follow a normal distribution.

  4. What does the confidence level of 95% mean in the context of hypothesis testing?

    Answer: If the study were repeated many times, 95% of the intervals would contain the true parameter

    A 95% confidence level means that in repeated sampling, approximately 95% of the constructed intervals would capture the true population parameter.

  5. When should a Black Belt use a one-tailed test instead of a two-tailed test?

    Answer: When there is a specific directional hypothesis supported by prior knowledge

    A one-tailed test is appropriate when there is a strong theoretical or practical reason to test for an effect in only one specific direction.

  6. What is the null hypothesis in a one-way ANOVA test?

    Answer: All group means are equal

    The null hypothesis in one-way ANOVA states that all population group means are equal, and any observed differences are due to random variation.