# Thread: p- value

1. ## p- value

on Hypothesis testing, I know how to find p-value... and when to reject null hypothesis, etc. I know how to solve it and find it. I can get the problem right.
The problem is I do not know what it means(p-value and level of significant). The purpose of finding p-value is to reject or not reject null hypothesis(compare to given alpha)? What is the p-value representing?

And I still do not fully comprehend about given alpha(level of significant). From what I know is given alpha(say 0.05) is saying I will risk 5% of rejecting null hypothesis when in deed, null hypo. is right.

'the sample evidence is sufficient at the 0.05 level to justify rejecting null hypothesis'------------what is it saying? sufficient at the 0.05 level?

'at the 1% level of significance, evidence shows average assembly time is less thatn 38 hours.'---------------what is mean 'at the 1% level of significance'?

I really want to understand these. Thank you for your precious time and effort to answering my questions,

I thank you all in advance,

2. Originally Posted by Judi
on Hypothesis testing, I know how to find p-value... and when to reject null hypothesis, etc. I know how to solve it and find it. I can get the problem right.
The problem is I do not know what it means(p-value and level of significant). The purpose of finding p-value is to reject or not reject null hypothesis(compare to given alpha)? What is the p-value representing?

And I still do not fully comprehend about given alpha(level of significant). From what I know is given alpha(say 0.05) is saying I will risk 5% of rejecting null hypothesis when in deed, null hypo. is right.

'the sample evidence is sufficient at the 0.05 level to justify rejecting null hypothesis'------------what is it saying? sufficient at the 0.05 level?

'at the 1% level of significance, evidence shows average assembly time is less thatn 38 hours.'---------------what is mean 'at the 1% level of significance'?

I really want to understand these. Thank you for your precious time and effort to answering my questions,

I thank you all in advance,

The p-value is the probability of getting a test statistic as far or further from what is expected given that the null hypothesis holds as that observed.

Thus if p is low we are supposed to conclude that the null hypothesis is implausible. How low it has to be for us to reach this conclusion is a matter of choice and depends on the importance of the result and the experimenters predudices. If in doubt it is common to reject the null hypothesis if p<=0.05.

RonL

3. Thanks, just one more:

If we say' 'at the 1% level of significance, evidence shows to reject null hypothesis' Would you elaborate what this means? especially 'at the 1% level of significance'?

Thank you and thank you!!!

4. Originally Posted by Judi
Thanks, just one more:

If we say' 'at the 1% level of significance, evidence shows to reject null hypothesis' Would you elaborate what this means? especially 'at the 1% level of significance'?

Thank you and thank you!!!
It means that:

1. You decided at the start of the statistical analysis that you would reject the null hypothesis and therefore accept the alternative hypothesis if p < 0.01.

2. After doing the calculations, you found p < 0.01.

By the way, don't be offended when I say that the thanks I gave your post was actually for the good Captain's edit (I got a good laugh from it - getting a laugh is always useful in my book).

5. ## significance test

just a pondering...
Does 1% level of significance test state the statement stronger than 5%?
Which one is more significant when comparing 1% to 5%?

6. Yey! At last a question I know the answer to. The p value you have is the value given for the result you found happening by chance alone which means that your findings may not be meaningful if the p value is too high. p<0.05 means that there is less than 5% probability that the result happened by chance alone. p<0.01 means that there is less than a 1% probability of your findings happening by chance. Therefore a p value of <1% is a stronger finding than a p value of < 5%. Most studies expect/accept a p value of < 5% for the results to be deemed significant.