Derivation of partitioning of total variability

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The discussion focuses on deriving the equation for the sum of squares in ANOVA (Analysis of Variance). A key point mentioned is the identity -\bar{Y}_{i.} + \bar{Y}_{i.} = 0, which can be manipulated without altering the equation's integrity. Participants seek clarification on how to construct a working equation to reach the sum of squares identity. The conversation emphasizes the importance of understanding this derivation in the context of statistical analysis. Mastering these concepts is essential for accurate data interpretation in ANOVA.
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it is a sum of squares in anova(analysis of data). how can i derive this equation?tnx..
 

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-\bar{Y}_{i.} + \bar{Y}_{i.} = 0

So you can place that anywhere and you change nothing, it is a common trick.
 
viraltux said:
-\bar{Y}_{i.} + \bar{Y}_{i.} = 0

So you can place that anywhere and you change nothing, it is a common trick.
what is my working equation so i can arrive at the sum of squares identity?
 

Thread 'Deductive proof in logic formal systems'

I was reading documentation about the soundness and completeness of logic formal systems. Consider the following $$\vdash_S \phi$$ where ##S## is the proof-system making part the formal system and ##\phi## is a wff (well formed formula) of the formal language. Note the blank on left of the turnstile symbol ##\vdash_S##, as far as I can tell it actually represents the empty set. So what does it mean ? I guess it actually means ##\phi## is a theorem of the formal system, i.e. there is a...
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