MHB Covariance and Correlation matrix

AI Thread Summary
Covariance and correlation matrices are essential tools for understanding the relationship between variables in statistics. They provide insights into how much two variables change together and the strength of their linear relationship. Calculating these matrices can be done using statistical software like R Studio, which offers functions for easy computation. The Pearson coefficient helps determine the proportion of variance explained by the correlation, indicating the strength of the relationship. For comprehensive explanations, resources like Wikipedia and various online articles can provide valuable information.
theakdad
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I would love to learn more about those two matrices. What do they tell us,how to calculate them? Maybe in R Studio?
I was searching for some good explanations on google,but i didnt find them.

And another question,i apologize if is not in right forum...
How do i know how much dispersion can i explain with Pearson coefficient?

Thank you for the answers.
 
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Thread 'Formal derivation of statement from Peano Arithmetic system'

I was reading a Bachelor thesis on Peano Arithmetic (PA). PA has the following axioms (not including the induction schema): $$\begin{align} & (A1) ~~~~ \forall x \neg (x + 1 = 0) \nonumber \\ & (A2) ~~~~ \forall xy (x + 1 =y + 1 \to x = y) \nonumber \\ & (A3) ~~~~ \forall x (x + 0 = x) \nonumber \\ & (A4) ~~~~ \forall xy (x + (y +1) = (x + y ) + 1) \nonumber \\ & (A5) ~~~~ \forall x (x \cdot 0 = 0) \nonumber \\ & (A6) ~~~~ \forall xy (x \cdot (y + 1) = (x \cdot y) + x) \nonumber...
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