I chanced upon this question:
A two-tailed t-test of the null hypothesis that the population mean differs from zero has a p-value of 0.0275. Using a significance level of 5%, the most appropriate conclusion is: A. reject the null hypothesis. B. accept the null hypothesis. C. the chosen significance level is too high. Answer = A A is correct. The p-value is the smallest level of significance at which the null hypothesis can be rejected. In this case, the given p-value is less than the given level of significance and we reject the null hypothesis. Just wondering: When they quote p-value, do we assume 2 sided p-values ? Because i took 5% sig level and divdided by 2, and answered B instead of A. Since 0.0275 < 0.025.
The p-value and significance level account for the total margin of error.
what do you mean? sorry i don’t quite understand.
Why don’t we use the significance level of 1.96?
P-value has nothing to do with two tailed test they put that there to confuse you. If p-value is less than significance level, reject.
and the P-value in this case is 0.05? Because if it’s 0.025 then P-value > significance level.
You simply compare the (unaltered) p-value to the (unaltered) level of significnace.
Here, you compare 2.75% to 5%.
If they’d changed it to a one-tail test (and left everything else the same), you’d still compare 2.75% to 5%.
geez, you saved the day again S2K…thanks!
thanks to everyone here and faptor for the posting too. There’s your answer!
Noted. Thanks again! Greatly appreciated.
since it is two tailed test divide both values by 2 and you will get p-value=.0275/2=0.01375 which is less than CV, 0.05/2=0.025. since pv<cv i.e. 0.01375<0.025, reject the null hypothesis. That’s it…