We do statistical testing when we have an initial ‘guess-timate’ of how the results of the study might, or should, turn out. We call such guess-timates a hypothesis.

Such hypotheses come in pairs:

The null hypothesis says there will be “none of” something. For example: no statistically significant between-group difference, relationship between something and something, or impact or effect of something on something. Sometimes we call this the “pessimistic” outcome.

In contrast, the alternative hypothesis says there “will be” something: a statistically significant between-group difference, relationship between something and something, or impact or effect of something on something. Sometimes we call this the “optimistic” outcome.
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We look at the value of the test statistic to decide which hypothesis to believe, based on the data. We will either retain the null hypothesis, or reject it in favor of the alternativehypothesis.When testing a null hypothesis against its alternative hypothesis, your decision is to either REJECT the null hypothesis or FAIL TO REJECT the null hypothesis. Why don’t we claim to ACCEPT the null hypothesis? Give an analogy to explain this concept.