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How to Conduct a Simple Hypothesis Test in Six Sigma
I was teaching a Six Sigma Green Belt methods course in Washington, DC and was asked to simplify the basic road map in Hypothesis TestingHypothesis testing definition A statistical hypothesis test ..., so I thought; this is a great idea to publish as a blog post so that more people can have access to this valuable information.
In the example below, we are testing whether or not there is a correlation between two continuous variables.
Hypothesis Test Example
1. What is the practical question?
– Does an increase in tire pressure cause an increase in tread wear?
2. What is the X? (Input being Controlled)
– Tire Pressure
3. What is the Y? (What is being Measured)
– Tread Wear
4. Gather Data, Run the Analysis and determine the Pearson Correlation Co-efficient and P-Value
5. Run a Correlation Analysis (selecting Pearson method). In this example the Pearson value ( r ) = 0.554 with a P-value = 0.0228
6. The results indicate that there is a medium correlation of the two factors and that the data set is significant at an Alpha riskAlpha risk (α) is the risk of incorrectly deciding to rejec... levelStatistics level A statistics level is the value of input in... of .0228.
A guideline of R Values:
- between -0.2 and +0.2 is random chance of a relationship
- between -0.8 and -1.0 or +0.8 and +1.0 is a strong relationship
- the remaining levels / values indicate there is a weak to moderate relationship
Remember that correlation is not causation. It is only a test of the strength of the linear relationship of two continuous factors; so the R Value indicates the strength of the relationship and the P Value indicates the Alpha Level the relationship can be stated to be significant.
We hope this simplifies the concept and serves as a guide to conducting a Hypothesis TestHypothesis testing definition A statistical hypothesis test ... in a Six SigmaSix Sigma Definition: Six Sigma is a set of techniques and t... Learn More... method. What problems (or opportunities) would you apply this to in your organization?
Share your thoughts in the comments below!
Pearson sample correlation coefficient is a measure of the strength of a linear relationship. We must always create a scatter plot to check the form of the relationship to assure that r will be an appropriate metric. For example, a second order (parabolic) relationship may have an r value close to zero which would lead an analyst to erroneously conclude there is no relationship between the variables.
I am working with injection moulding production, but i am not sure how i can use hypotesis testing there ?
Jakob, Great question. We work with several companies that have injection mold processes. You can use many different hypothesis tests based on your hypothesis. For example, If you are looking at a dimensional attribute of a molded part (like a plastic bottle) then you may have the hypothesis that there is a difference per shift in the dimensional attribute of the molded part (although there should be little to no variation per shift). You could capture data per shift (let’s say there are three shifts) and use the ANOVA to determine if there is a statistically significant difference between shifts.