True/ false (a) The p-value quantifies the degree ofevidence provided by the sam

Question

True/ false

(a)     The p-value quantifies the degree ofevidence provided by the sample against the null hypothesis. Thesmaller the p- value, the weaker the evidence.

(b)     A confidence interval for aparameter gives a set of plausible value of the parameter at agiven confidence level.

(c)     A test if significance makes adecision about whether a claimed value is a plausible value of theparameter considered.

(d)     When we say that the evidenceprovided by the sample is sufficiently strong, we mean the resultis significant and the null hypothesis should be rejected.

(e)     Large sample tend to producesignificant results.

(f)       Statistical significancedoes not tell us whether an effect is large enough to beimportant.

(g)     Statistical significance andpractical significance are not the same.

(h)     Running 20 independent tests andreaching the 25% level of significance only once is not goodevidence that you have found something. This is because by chancewe would see 1 test significant among 20 non significant at 5%level of significance.

Explanation / Answer

(a)     The p-value quantifies the degreeof evidence provided by the sample against the null hypothesis. Thesmaller the             p-  value, the weaker the evidence.
       False (b)     A confidence interval for aparameter gives a set of plausible value of the parameter at agiven confidence level.
       True (c)     A test if significance makes adecision about whether a claimed value is a plausible value of theparameter considered.
      True (d)     When we say that the evidenceprovided by the sample is sufficiently strong, we mean the resultis significant and th    null hypothesis should berejected.
         True (e)     Large sample tend to producesignificant results.
         True (f)       Statisticalsignificance does not tell us whether an effect is large enough tobe important.
          False (g)     Statistical significance andpractical significance are not the same.
         True (h)     Running 20 independent tests andreaching the 25% level of significance only once is not goodevidence that you have found something. This is because by chancewe would see 1 test significant among 20 non significant at 5%level of significance          True

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