MHB -aux.05 coefficient of determination is 83.0 %

AI Thread Summary
The coefficient of determination, R², is 83.0%, indicating that 83% of the variability in the dependent variable (y) can be explained by the independent variable (x) in the regression model. This suggests a strong correlation between x and y, meaning the regression line fits the data well. The discussion highlights confusion about how R² is calculated, specifically referencing the formula involving sums of squares (SS). Clarification on the meaning of "S" in this context is sought, indicating a need for further understanding of statistical concepts. Overall, the high R² value reflects a significant relationship between the variables analyzed.
karush
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The coefficient of determination is 83.0 \%.
Provide an interpretation of this value.
$\begin{array}{rrrr}
x & y \\
12.17 & 1.88 \\
11.70 & 1.82 \\
11.63 & 1.77 \\
12.27 & 1.93 \\
12,03 & 1.83 \\
11.60 & 1.77 \\
12.15 & 1.83 \\
11.72 & 1.83 \\
11.30 & 1.70
\end{array}$

here is my desmos plot and I can see that R^2 is $83.0\%$
but after looking at some examples I don't see how it is derived

However, the interpretation of this is
of the variability in y is explained by the least-squares regression line.
nw5desmos.png
 
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ok I think we are supposed to use this
$r= \dfrac{SS_{xy}}{\sqrt{SS_{xx}SS_{yy}}}$

not sure what S is
 
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