Explain Misconceptions about significance testing?

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eurgylchnj · Accepted Answer

Misconceptions about significance testing is,
The probability value is defined as the probability that the null hypothesis is false.
The correct explanation is that, the probability of a result as extreme or more extreme given that the null hypothesis is true is known as the probability value.
The probability value is the probability of the data given the null hypothesis and it is not the probability that the null hypothesis is false.
If the probability value is low, then it is indicate the larger effect.
The correct explanation is that, if the probability value is low, then it is indicate that the sample outcome would be very unlikely if the null hypothesis were true.
For the small effect sizes, the low probability value can occur, particularly if the sample size is large.
The meaning of the non-significant outcome is that the null hypothesis is probably true.
The correct explanation is that, the meaning of the non-significant outcome is that the data do not finally demonstrate that the null hypothesis is false.

Explain Misconceptions about significance testing?

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