Correlation and the Line of Best Fit
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This example demonstrates how to visualize data correlation through scatter plots and draw the line of best fit. Core math concepts include Pearson's correlation coefficient (PMCC), mean, standard deviation, and linear regression. GeoGebra commands and objects used are If, Sequence, MeanY, SampleSDY, MeanX, PMCC, SampleSDX, SampleSDY, Sum, TableText, Textfield, Mirror, Max, mean, SDX, SDY. Suitable for high school mathematics teaching, focusing on data analysis and statistical modeling.
GeoGebra Commands & Parameters
If(xvalues ≥ 1, Element[list1, 1], 0) → G4If(xvalues ≥ 2, Element[list1, 2], 0) → G5If(xvalues ≥ 3, Element[list1, 3], 0) → G6If(xvalues ≥ 4, Element[list1, 4], 0) → G7If(xvalues ≥ 5, Element[list1, 5], 0) → G8If(xvalues ≥ 8, Element[list1, 8], 0) → G11If(xvalues ≥ 9, Element[list1, 9], 0) → G12If(xvalues ≥ 10, Element[list1, 10], 0) → G13If(xvalues ≥ 11, Element[list1, 11], 0) → G14If(xvalues ≥ 6, Element[list1, 6], 0) → G9If(xvalues ≥ 7, Element[list1, 7], 0) → G10If(xvalues ≥ 15, Element[list1, 15], 0) → G18If(xvalues ≥ 12, Element[list1, 12], 0) → G15If(xvalues ≥ 13, Element[list1, 13], 0) → G16If(xvalues ≥ 14, Element[list1, 14], 0) → G17If(xvalues ≥ 16, Element[list1, 16], 0) → G19If(xvalues ≥ 17, Element[list1, 17], 0) → G20If(xvalues ≥ 18, Element[list1, 18], 0) → G21If(xvalues ≥ 19, Element[list1, 19], 0) → G22If(xvalues ≥ 20, Element[list1, 20], 0) → G23If(xvalues ≥ 1, Element[list2, 1], 0) → H4If(xvalues ≥ 2, Element[list2, 2], 0) → H5If(xvalues ≥ 3, Element[list2, 3], 0) → H6If(xvalues ≥ 4, Element[list2, 4], 0) → H7If(xvalues ≥ 6, Element[list2, 6], 0) → H9If(xvalues ≥ 7, Element[list2, 7], 0) → H10If(xvalues ≥ 8, Element[list2, 8], 0) → H11If(xvalues ≥ 9, Element[list2, 9], 0) → H12If(xvalues ≥ 10, Element[list2, 10], 0) → H13If(xvalues ≥ 11, Element[list2, 11], 0) → H14If(xvalues ≥ 12, Element[list2, 12], 0) → H15If(xvalues ≥ 13, Element[list2, 13], 0) → H16If(xvalues ≥ 14, Element[list2, 14], 0) → H17If(xvalues ≥ 15, Element[list2, 15], 0) → H18If(xvalues ≥ 16, Element[list2, 16], 0) → H19If(xvalues ≥ 17, Element[list2, 17], 0) → H20If(xvalues ≥ 18, Element[list2, 18], 0) → H21If(xvalues ≥ 19, Element[list2, 19], 0) → H22If(xvalues ≥ 20, Element[list2, 20], 0) → H23If(xvalues ≥ 5, Element[list2, 5], 0) → H8Sequence(Element[list2, j], j, 1, xvalues) → list4MeanY(list5) → meanySequence(Element[list1, i], i, 1, xvalues) → list3SampleSDY(list5) → SyMeanX(list5) → meanxPMCC(list3, list4) → rSampleSDX(list5) → SxSum(F4:F23) → F25If(s1, meanx + "", "\lightgreen{Δ}") → J28If(s2, meany + "", "\lightgreen{Δ}") → J29If(s3, SampleSDX[list5] + "", "\lightgreen{Δ}") → J30If(s4, SampleSDY[list5] + "", "\lightgreen{Δ}") → J31If(s5, r + "", "\lightgreen{Δ}") → J32If(s7, m + "", "\lightgreen{Δ}") → J33If(s6, intercept + "", "\lightgreen{Δ}") → J34TableText({{I28, J28}, {I29, J29}, {I30, J30}, {I31, J31}, {I32, J32}, {I33, J33}, {I34, J34}}, "|_") → text5If(xvalues ≥ 6, Element[list1, 6], 0) → text6If(xvalues ≥ 6, Element[list1, 6], 0) → ""If(xvalues ≥ 4, Element[list2, 4], 0) → text8Textfield(o) → InputBox1Mirror(f, h) → f'Textfield(aa) → InputBox2Max(list1) → xmaxMax(list2) → ymaxmean(B4:B23) → F28mean(C4:C23) → G28SDX(list5) → F29SDY(list5) → G29mean(B4:B23) → B26