Pvalue in ANOVA table
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 This topic has 12 replies, 11 voices, and was last updated 14 years, 1 month ago by Ernikunj.

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September 15, 2003 at 4:44 am #33298
What actually the “P” value tells us in ANOVA table. We normally compare the test statistics with the critical value (F0, obtained from Ftable at given d.o.fs) to determine whether the given parameters effects are significant or not.
Thanks0September 15, 2003 at 1:17 pm #89864What used to be done, before computers, was that you would look up a critical value and compare it to your observed Fstatistic. That critical value represented the cutoff point for the alpha level of significance, usually 0.05. Well, 0.05 is also the pvalue that is associated with a certain Fstatistic. When you see a pvalue in an ANOVA table what you see is really the area under the F distribution curve that is to the right of your observed Fstatistic. It also represents the probability that your observed Fstatistic occurs under the assumption that the null hypothesis of your test (in this case, that the means of the factor levels are equal).
0September 15, 2003 at 5:38 pm #89877
Muhammad A khanParticipant@MuhammadAkhan Include @MuhammadAkhan in your post and this person will
be notified via email.The pvalue is the area to the right of the F statistic, F0, obtained from ANOVA table. It is the probability of observing a result (Fcritical) as big as the one which is obtained in the experiment (F0), assuming the null hypothesis is true. Low pvalues are indications of strong evidence against the null hypothesis. I read in the book that it is common to declare a result as significant if the pvalue is less than 0.05 or 0.01.
Hope this helps0September 15, 2003 at 8:57 pm #89881
jediblackbeltParticipant@jediblackbelt Include @jediblackbelt in your post and this person will
be notified via email.This is more of a question than a statement, but I was always taught if you use a PValue in the ANOVA then you are assuming normality in the data. Correct???
0September 15, 2003 at 9:16 pm #89883
Muhammad A khanParticipant@MuhammadAkhan Include @MuhammadAkhan in your post and this person will
be notified via email.In Analysis of variance test (ANOVA), we have two fundamental assumptions. First that the “means” are normally distributed; secondly the “variances” are equal. So, what I think is that in ANOVA test, we can use both methods, either “F” test or “P” test in oder to see whether the means are significantly different or not. Please correct me if i am wrong!
Regards0September 22, 2003 at 1:53 pm #90142
Peter MooreParticipant@PeterMoore Include @PeterMoore in your post and this person will
be notified via email.See this link. It offers one of the best explanations I’ve seen.
http://www.sportsci.org/resource/stats/pvalues.html0September 22, 2003 at 9:05 pm #90159P values have 2 specific uses.
1. Normality of Data – a significant P value (P < or = .05) means that the sample data you are testing (either with Normal Probability Plot or Descriptive Stats, using Minitab) is a normal subset of the population data.
2. Hypothesis Testing – a significant P value (P < or = .05) means you would reject your null hypothesis (that there is NO difference between the 2 or more sets of data you are testing).0September 22, 2003 at 11:26 pm #90161
Raja SetlurParticipant@RajaSetlur Include @RajaSetlur in your post and this person will
be notified via email.In Bobby’s reply, paragraph1, is it that P < or = 0.05 implies normal data or
P > or = 0.05 implies normal data?
Thanks
0September 23, 2003 at 12:31 am #90166I agree with 2nd statement, but a P Value in a normality test must be >=.05 to indicate normality.
0September 23, 2003 at 2:04 am #90169The P value is the probability of Alpha (or type 1) error, which is the probability that an F value this large could occur by chance and not be due to some assignable cause.
0September 24, 2003 at 10:56 am #90225Yes, I will say I placed my sign backwards. Just goes to show that in a few instances inspection may be a valueadded step.
Always proofread your email before you hit send.
Thanks Dan and Raja for catching my miscue.0September 24, 2003 at 6:36 pm #90241I remember it this way.If the p is low, the null must go.
0October 17, 2008 at 1:30 am #176784
ErnikunjParticipant@Ernikunj Include @Ernikunj in your post and this person will
be notified via email.In 2nd use…I would like to add that…pValue is probability of making a type I error that is calculated from data.
so pvalue is probability of rejecting a true hypothesis.0 
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