P<0.05 is a number sccientists are looking for no matter they are reading an article by others or conduct a research of their own. When p<0.05 appeared either at the bottom of a table or in a chart, we know that a conclusion is there; otherwise, futher research is needed. What makes this tiny number so important?
In research, we work on a sample to see the population. As indicated in another blog, 95% confidence interval will be used if our interest is in a single character, such as how many people support the president (click here to read more about that). However, if we want to compare two or more groups, or want to test if two things are related with each other, p value is commonly accepted as the standard to judge if an observed difference between two groups or a correlation/regression coefficient is true or a result that can be generated simply due to random samppling. The p value indicates the likelihood or the chance to get the observed results purely due to randomly sampling (also termed as sampling error).
Why 5%? I have not read any objective assessment. One thing for sure is that this 5% is complementary to 95%, the confidence interval, each telling the same story from different angle for different situations. As has been described in other places, the digit 5 in numerology represent the majority. If the chance to obtain the observed result is less than majority, this means to get the research result by chance is rare (opposite of majority) or very unlikely. Therefore, the observed result is true. However, we have to remember that this does not mean we are absolutely right when we draw this conclusion, becuase we have up to 5% chances to make mistakes!
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