The managers huddled to see if they had won or lost. Did the new process from 2 months before yield data showing a reduction in cost? Or was it merely a matter of chance… Too soon to do the data dance? So they set about the business of crafting a hypothesis test
- “Type I Error Blues,” by David Stein
The managers huddled to see if they had won or lost.
Did the new process from 2 months before yield data showing a reduction in cost?
Or was it merely a matter of chance…
Too soon to do the data dance?
So they set about the business of crafting a hypothesis test
In order to conclude which process was best.
With the null hypothesis meaning “status quo”, no change evident
They quickly concluded H0 could not stand, as was their true intent.
Just one month later, they realized their grave mistake!
A Type II error would have been so much safer, for goodness sake.
Alas, their final huddle was a sad one with HR Director Bob.
He told them to go back to training school as each was now in need of a new job.
- What was the likely managerial mood and outcome on the days immediately following the (erroneous) conclusion to reject this null hypothesis?
- What would have been the likely managerial mood and outcome on the days immediately following an (erroneous) conclusion not to reject the null hypothesis?
- In the presence of a Type II Error, what do you suppose would have happened to their cost reduction/process improvement efforts 3-6 months down the road? Please explain in everyday English.
State the null and alternative Hypotheses:
Null Hypothesis:
H0: There is no change in the cost due to new process.
Alternative Hypothesis:
H1: There is a reduction in cost due to new process.
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