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Section 4.2 Building Linear Models from Data

Section 4.2 Building Linear Models from Data. OBJECTIVE 1. Draw a scatter diagram of the data, treating on-base percentage as the independent variable. Use a graphing utility to draw a scatter diagram. Describe what happens to runs scored as the on-base percentage increases. OBJECTIVE 2.

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Section 4.2 Building Linear Models from Data

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  1. Section 4.2 Building Linear Models from Data

  2. OBJECTIVE 1

  3. Draw a scatter diagram of the data, treating on-base percentage as the independent variable. • Use a graphing utility to draw a scatter diagram. • Describe what happens to runs scored as the on-base percentage increases.

  4. OBJECTIVE 2

  5. Select two points and find an equation of the line containing the points. • Graph the line on the scatter diagram obtained in the previous example. • Using (34.7, 865) and (32.7, 691) • m = 865 – 691 = 87 • 34.7 – 32.7 • y = 87x + b • 865 = 87(34.7) + b  b = -2153.9 • y = 87x – 2153.9

  6. y = 87x – 2153.9

  7. OBJECTIVE 3

  8. Use a graphing utility to find the line of best fit that models the relation between on-base percentage and runs scored. • Graph the line of best fit on the scatter diagram obtained in the previous example. • Interpret the slope. • Use the line of best fit to predict the number of runs a team will score if their on-base percentage is 33.5.

  9. For the following data: • Draw a scatter diagram. • Select two points from the scatter diagram and find the equation of the line containing the points selected. • Using (7,3) and (9,6); m = 6 - 3 = 3/2. y = 3/2x + b • 9 - 7 • (7,3): 3 = 3/2(7) + b  b = -15/2 y = 1.5x – 7.5

  10. (c) Graph the line found in part (b) on the scatter diagram. y = 1.5x – 7.5 (d) Use the calculator to find the line of best fit. y = 1.13x – 3.86 (e) Using the best fit line found in (d) on the same scatter diagram

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