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Can you compare two different p values?
In your particular case there is absolutely no doubt that you can directly compare the p-values. If the sample size is fixed (n=1000), then p-values are monotonically related to t-values, which are in turn monotonically related to the effect size as measured by Cohen’s d.
What does an insignificant p-value mean?
A p-value less than 0.05 (typically ≤ 0.05) is statistically significant. A p-value higher than 0.05 (> 0.05) is not statistically significant and indicates strong evidence for the null hypothesis. This means we retain the null hypothesis and reject the alternative hypothesis.
How do you write an insignificant p-value?
For P values less than . 001, report them as P<. 001, instead of the actual exact P value. Expressing P to more than 3 significant digits does not add useful information since precise P values with extreme results are sensitive to biases or departures from the statistical model.
Can you compare the effect sizes of p values?
Instead of comparing p-values you should compare the effect sizes. For correlations for example, May and Hittner (1997) are comparing different tests http://www.tandfonline.com/doi/abs/10.1080/00220973.1997.9943458#.VLFh1nv3I-o I have my doubts whether the classification of p-values does make any sense at all. p-values rely on sample size.
How do you know if a p value is statistically significant?
How do you know if a p-value is statistically significant? The level of statistical significance is often expressed as a p-value between 0 and 1. The smaller the p-value, the stronger the evidence that you should reject the null hypothesis. A p-value less than 0.05 (typically ≤ 0.05) is statistically significant.
How to get ” exact ” p values from multiple comparisons?
Prism 5 let you choose the significance level (0.05, 0.01, or 0.001). Whatever significance level you choose, it also displays asterisks to denote the smallest of those significance levels at which the comparison is statistically significant. How to report “exact” P values from multiple comparisons?
When to use p value in chi square test of difference?
If chi square value is to be tallied with the table value at 0.05 level of significance and the table value is less, then the result is significant or not, and then what is the use of the p-value written besides it. Guidance will be highly appreciated.