Statistics - critical value method and P-value method?

We have studied two different methods for making statistical inferences such as developing interval estimates and conducting hypothesis tests. These methods are the "Critical Value Method" and the "P-Value Method". In one page or less explain these two vital concepts and, most importantly, their relationships to each other.

Statistics - critical value method and P-value method?
If you check answers that I give to stats questions you will see that I do NOT just give the answer but provide all the detail behind the answer. But for your question, I think it is more appropriate if YOU write what you think the answer to your question is and let us STAT Geeks review your answer and provide input. You can't expect someone seriously to give you the answer to this question and even if they did write a whole page "could" you believe it.....??????





In all honesty, I think you should post your explanation and I know I will read the whole thing and spend time reviewing it for errors or areas for improvement.
Reply:the critical value method is very useful in that you can find the value of the sample statistic that will reject the null hypothesis so if you are repeating the same experiment many times in the field you can find out the conclusion of the hypothesis test right then without having to make any other calculations.





the p-value method, i think, is more useful in that by reporting the p-value you allow others to draw their own conclusions. perhaps you want to test at the 2% level, but the read wants to test at the 5% level, by reporting the p-value you can both make conclusions. the fix level, or critical value, method does not allow for this.





the relationship is that if you test at the, say 5% level, you will have the same conclusion from either method. the critical value method is not as good for papers, but the p-value method requires more calculations in the field to get a quick solution.