Introduction to Hypothesis Testing and Tests for Means in Six Sigma

Candidates seeking Six Sigma Green Belt certification; quality professionals, engineers, production managers, and frontline supervisors; process owners and champions charged with the responsibility of improving quality and processes at the organizational or departmental level

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Expected Duration
116 minutes

During the Analyze phase of a Six Sigma improvement project, the team conducts a number of statistical analyses to determine the nature of variables and their interrelationships in the process under study. Team members typically collect samples of the population data to be analyzed, and based on that sample data, they make hypotheses about the entire population. Because there is a lot at stake in forming the correct conclusions about the larger population, Six Sigma teams validate their inferences using hypothesis tests. This course introduces basic hypothesis testing concepts, terminologies, and some of the most commonly used hypothesis tests – one- and two-sample tests for means. The course also discusses the importance of sample size and power in hypothesis testing, as well as exploring issues relating to point estimators and confidence intervals in hypothesis testing. This course is aligned to the ASQ Body of Knowledge and is designed to assist Green Belt candidates toward their certification and to become productive members on their Six Sigma project teams.


Key Concepts in Hypothesis Testing

  • identify the purpose of hypothesis testing
  • match elements of a hypothesis test with corresponding descriptions
  • identify best practices when establishing the practical significance of hypothesis testing results
  • demonstrate your understanding of basic concepts related to hypothesis testing

Confidence Interval and Error Types

  • recognize how confidence intervals are used in hypothesis testing
  • recognize the attributes of Type I and Type II errors
  • classify estimates and error types

Power and Sample Sizes

  • identify factors that affect the power of a hypothesis test
  • determine sample size for a given alpha risk level using margin of error formula
  • determine the power and appropriate sample size for a given hypothesis test

The Hypothesis Testing Process

  • sequence the steps in the hypothesis testing process
  • match examples of alternative hypotheses with their corresponding probability distribution graphs
  • determine whether to reject a null hypothesis based on given critical values and p-values
  • use steps in the hypothesis testing process

One-sample Tests for Means

  • perform a one-sample hypothesis test for mean, given a scenario
  • carry out one-sample hypothesis tests for means

Two-sample Tests for Means

  • test a hypothesis using a two-sample test for means (pooled)
  • carry out a two-sample hypothesis test for means
  • test a hypothesis using a two-sample test for means (non-pooled)
  • carry out a two-sample hypothesis test for means





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