Ash O.

asked • 04/30/15

ANOVA Interpretation

What do these mean ? 
 
 
ANOVA:
 
1. F-Statistic
 
2. P-value
 
When the P-value is below 0.05, it means there is no relationship between the independent and dependent variable, right? 
 
Thank you in advance to the person who answers these question for me. 

Stephanie M.

tutor
I was going to let someone more statistically-inclined answer your questions, but I'm afraid they'll get lost in the shuffle. I'll leave my answer as a comment so your question still shows up as "unanswered" just in case someone else comes along who knows more than I do.
 
In general, when you're performing a statistical analysis, you'll start out with a null hypothesis (usually, that the results you've gathered are not statistically significant) and an alternative hypothesis. If you reject the null hypothesis, it means you've proven that your results are special. They can't be explained by normal variation. They are statistically significant.
 
The F-Statistic and the P-value are ways of measuring statistical significance.
 
The F-Statistic (which I know less about) basically compares two mean square values: a normal mean square value and your data's mean square value. If the F-Statistic is near 1, then the distributions are very similar. If you find that the F-Statistic = (variation among groups)/(variation within groups) ≈ 1, this tells you that most of the variation in your data can be explained by normal variation. If the F-Statistic is very large, that tells you that your data is statistically significant. The large amount of variation in your data can't be described by normal variation, so something else must be going on.
 
The P-value is the probability that the data you're observing could come up by random chance, given that nothing is significant about your data. So if your P-value is, say, 0.23, that means that there's a 23% chance that you'd see data like yours if nothing significant was going on. That means you'd be pretty uncertain that your data actually proved something significant. If your P-value is something like 0.05 or 0.01, you can be much more confident that your results can't be explained by random variance. A small P-value means there's a small chance your data's variation can be described by normal variation, so you can reject the null hypothesis and say that your data is statistically significant: there must be something weird going on.
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05/02/15

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Oscar A. answered • 05/03/15

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The ANOVA test is used to determine the impact independent variables have on the dependent variable in a regression analysis

Read more: http://www.investopedia.com/terms/a/anova.asp#ixzz3Z7D5rDXT
Follow us: @Investopedia on Twitter
 

1. F-Statistic: Under Certain Conditions: The F  Statistic has a repeated sampling distribution.

 

P-Value: Is often referred to as the OBSERVED SIGNIFICANCE LEVEL OF THE TEST. There

are the Large sample and small sample UPPER,LOWER, TWO-TAILED, and the Z computed value of the Z statistic

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