SIX SIGMA ICYB IASSC Certified Lean Six Sigma Yellow Belt

Bias in Sampling is an error due to lack of independence among random samples or due to systematic sampling procedures.

To draw inferences about a sample population being studied by modeling patterns of data in a way that accounts for randomness and uncertainty in the observations is known as ____________________.

For a Normal Distribution the Mean, Median and Mode are the same data point.

When two Inputs have an impact on the Output together yet seem to have no or little impact on their own this is called a/an ________________.

Hypothesis Testing can save time and help avoid high costs of experimental efforts by using existing data.

It is a Type II error if we decide to reject the Null Hypothesis when it is actually true.

A Belt experienced an Alpha of .05 and a Beta of .10 and knew these are the most common risk levels when running a Statistical test.

Inferential Statistics is largely about Significance. There are both Practical and _______________ Significance to consider during an analysis of data in a Lean Six Sigma project.

The Central Limit Theorem helps us understand the ___________ we are taking and is the basis for using sampling to estimate population parameters.

Hypothesis Tests determine the probabilities of differences between observed data and the hypothesis being solely due to _________ based on the result of the P-values.