Why "bother" with a null hypothesis at all?whenever i am seeking to get into data (once more), i am constantly lost at speculation trying out.My simple question is - why can we form a null hypothesis as a negation of what we need to show within the first region, and most effective then can we show or disprove the null speculation?Why do we do it at all, in preference to just proving the authentic speculation?

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Why &quot;bother&quot; with a null hypothesis at all?whenever i am seeking to get into data (once more), i am constantly lost at speculation trying out.My simple question is - why can we form a null hypothesis as a negation of what we need to show within the first region, and most effective then can we show or disprove the null speculation?Why do we do it at all, in preference to just proving the authentic speculation?

indyterpep · Accepted Answer

You seem confused. Statistical methods do not set out to prove; one either rejects or fails to reject a hypothesis. This wording is Very Important™. (See also this and this.)I&#039;ll use the classical judicial analogy. The accused (hypothesis) standing before the judge can be taken as &quot;guilty&quot; or &quot;not guilty&quot; by the judge (hypothesis test). Even with this, we can&#039;t totally eliminate the possibility of committing a Type I (innocent goes to jail) or Type II (guilty goes free) error. For all we know, even with all the evidence considered by the prosecution, defense, and jury, there might be a few confounding factors that weren&#039;t seen at the time. (Think of all the cases whose verdicts got changed when DNA tests became vogue.)Put another way, using the word &quot;accept&quot; misleads some people. Here, it means that we&#039;re accepting the possibility that it&#039;s true, not that it is certainly true.

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