Posted On: 01/05/2015 11:05:06 PM
Post# of 30065
I found this helped me with clearly understanding P values:
"With the high pressure to find low P values, there’s a tendency to view studies as either significant or not. Did a study produce a P value less than 0.05? If so, it’s golden! However, there is no magic significance level that distinguishes between the studies that have a true effect and those that don’t with 100% accuracy. Instead, it’s all about lowering the error rate to an acceptable level.
The lower the P value, the lower the error rate. For example, a P value near 0.05 has an error rate of 25-50%. However, a P value of 0.0027 corresponds to an error rate of at least 4.5%, which is close to the rate that many mistakenly attribute to a P value of 0.05.
A lower P value thus suggests stronger evidence for rejecting the null hypothesis. A P value near 0.05 simply indicates that the result is worth another look, but it’s nothing you can hang your hat on by itself. It’s not until you get down near 0.001 until you have a fairly low chance of a false positive."
blog.minitab.com/blog/adventures-in-statistics/five-guidelines-for-using-p-values
And this link: blog.minitab.com/blog/adventures-in-statistics/how-to-correctly-interpret-p-values
"With the high pressure to find low P values, there’s a tendency to view studies as either significant or not. Did a study produce a P value less than 0.05? If so, it’s golden! However, there is no magic significance level that distinguishes between the studies that have a true effect and those that don’t with 100% accuracy. Instead, it’s all about lowering the error rate to an acceptable level.
The lower the P value, the lower the error rate. For example, a P value near 0.05 has an error rate of 25-50%. However, a P value of 0.0027 corresponds to an error rate of at least 4.5%, which is close to the rate that many mistakenly attribute to a P value of 0.05.
A lower P value thus suggests stronger evidence for rejecting the null hypothesis. A P value near 0.05 simply indicates that the result is worth another look, but it’s nothing you can hang your hat on by itself. It’s not until you get down near 0.001 until you have a fairly low chance of a false positive."
blog.minitab.com/blog/adventures-in-statistics/five-guidelines-for-using-p-values
And this link: blog.minitab.com/blog/adventures-in-statistics/how-to-correctly-interpret-p-values
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