Hypothesis Process with Real World Examples
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Hypothesis testing process is a series of steps to evaluate a process to see if assumptions are correct. What are the major benefits of the process and what are the weakness of the process?
The null hypothesis or HO has unique characteristics such as (a) assumes status quo (b) assumes no difference (c) always contains an implied equal.
What would be an example in the average work world for HO and H1?
Using P-values for hypothesis testing they are intuitively easy and don't require critical values in charts. In real world terms, what is the best way to describe how P-values work and how to explain this to someone?
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This is a response on real life examples of how p-values work.
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The major benefits of the hypothesis testing process are that they can be used to confirm/reject claims or statements about observations. However, they can only be tested with a given level of significance, say 1%, 5%, 10%, etc. and therefore, there is always an element of uncertainty involved ...
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