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How does F statistic affect p-value?
The F value in one way ANOVA is a tool to help you answer the question “Is the variance between the means of two populations significantly different?” The F value in the ANOVA test also determines the P value; The P value is the probability of getting a result at least as extreme as the one that was actually observed.
What does a high F statistic value mean?
The F-Statistic: Variation Between Sample Means / Variation Within the Samples. The high F-value graph shows a case where the variability of group means is large relative to the within group variability. In order to reject the null hypothesis that the group means are equal, we need a high F-value.
Is F Distribution p-value?
The F Distribution Table does not directly give us a p-value. If you have an F statistic with a numerator degrees of freedom and denominator degrees of freedom and you would like to find the p-value for it, then you would need to use an F Distribution Calculator.
What does a high p value in statistics mean?
What High P-Values Mean and Don’t Mean One thing to note, a high p-value does not prove that your groups are equal or that there is no effect. High p-values indicate that your evidence is not strong enough to suggest an effect exists in the population.
What is the difference between a critical value and a F statistic?
F statistic, F-critical value, and P-value. The F-statistic is computed from the data and represents how much the variability among the means exceeds that expected due to chance. An F-statistic greater than the critical value is equivalent to a p-value less than alpha and both mean that you reject the null hypothesis.
Can a F statistic be greater than 1?
We don’t compare the F-statistic to 1 because it can be greater than 1 due only to chance, it is only when it is greater than the critical value that we say it is unlikely to be due to chance and would rather reject the null hypothesis.
Can a hypothesis test have a low p value?
Typically, when you perform a hypothesis test, you want to obtain low p-values that are statistically significant. Low p-values are sexy. They represent exciting findings and can help you get articles published. However, you might be surprised to learn that higher p-values, the ones that are not statistically significant, are also valuable.