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Scatter Plot of Vocabulary vs Reading Frequency with Regression Line

Scatter Plot of Vocabulary vs Reading Frequency with Regression Line
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2012-07-10 21:40
FunctionCoordinate GeometryProbability & StatisticsGraphing
In collections CCSS IP Math I Unit 4 Lesson 3
① This example demonstrates how to create a scatter plot of students' vocabulary size versus reading frequency and fit a linear regression line to reveal the correlation trend. ② Core mathematical concepts include the Pearson product‑moment correlation coefficient (PMCC), linear regression, scatter‑plot visualization, and interpretation of correlation. ③ Construction highlights: FitLineY draws the regression line, PMCC computes the correlation coefficient, Sequence generates the data points, Segment draws line segments, If and Polygon handle conditional display, RotateText rotates labels, and Textfield enables interactive input. ④ Suitable for high‑school statistics and probability courses, introductory college statistics, and introductory data‑analysis workshops.

GeoGebra Commands & Parameters

  1. FitLineY(PointList1) → LineFit
  2. PMCC(PointList1) → CorCoeff
  3. Textfield(A2) → InA2
  4. Textfield(A3) → InA3
  5. Textfield(A4) → InA4
  6. Textfield(A5) → InA5
  7. Textfield(A6) → InA6
  8. Textfield(A7) → InA7
  9. Textfield(A8) → InA8
  10. Textfield(A9) → InA9
  11. Textfield(A10) → InA10
  12. Textfield(A11) → InA11
  13. Textfield(A12) → InA12
  14. Textfield(A13) → InA13
  15. Textfield(A14) → InA14
  16. Textfield(A15) → InA15
  17. Textfield(A16) → InA16
  18. Textfield(A17) → InA17
  19. Textfield(A18) → InA18
  20. Textfield(A19) → InA19
  21. Textfield(A20) → InA20
  22. Textfield(A21) → InA21
  23. Textfield(B2) → InB2
  24. Textfield(B3) → InB3
  25. Textfield(B4) → InB4
  26. Textfield(B5) → InB5
  27. Textfield(B6) → InB6
  28. Textfield(B7) → InB7
  29. Textfield(B8) → InB8
  30. Textfield(B9) → InB9
  31. Textfield(B10) → InB10
  32. Textfield(B11) → InB11
  33. Textfield(B12) → InB12
  34. Textfield(B13) → InB13
  35. Textfield(B14) → InB14
  36. Textfield(B15) → InB15
  37. Textfield(B16) → InB16
  38. Textfield(B17) → InB17
  39. Textfield(B18) → InB18
  40. Textfield(B19) → InB19
  41. Textfield(B20) → InB20
  42. Textfield(B21) → InB21
  43. Sequence(Segment[(22, 0 + (7 * i)), (30, 0 + (7 * i))], i, 0, 10) → Linesh1
  44. Sequence(Segment[(32, 0 + (7 * i)), (40, 0 + (7 * i))], i, 0, 10) → Linesh2
  45. Sequence(Segment[(22 + (4 * i), 0), (22 + (4 * i), 84)], i, 0, 2) → Linesv1
  46. Sequence(Segment[(32 + (4 * i), 0), (32 + (4 * i), 84)], i, 0, 2) → Linesv2
  47. Segment((22, 84), (30, 84)) → top1
  48. Segment((32, 84), (40, 84)) → top2
  49. If(LineVisible, "Hide Best Fit Line", "Show Best Fit Line") → LineButton
  50. Polygon((21, y(Corner[1])), Corner[2], Corner[3], (21, y(Corner[4]))) → poly1, a, b, c, d
  51. RotateText("Books read", 0) → BottomLegend
  52. If(CorVisible, "Hide Correlation Coefficient", "Show Correlation Coefficient") → CorButton
  53. RotateText("Test score", 90*°) → SideLegend

AI Drawing Prompt Reference

Create a scatter plot showing the relationship between students' vocabulary size and reading frequency, with a linear regression line to reveal the correlation trend. Include axes, tick marks, grid lines, and a title for clear visualization of data points and the regression line. Use text fields for data input and conditional statements to control the display of certain elements. Start by drawing the axes and grid, then generate data points and fit the regression line, finally adding text fields and labels.
The prompt above was compiled from the original drawing commands and is for reference only.