Lesson 3: Linear Regression

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January 24, 2017 at 10:00 am  •  Posted in s17-busad360 by  •  0 Comments

Tue, Jan 24

Review:

  • Pearson Correlation Coefficient

Presentation:

  • Linear regression
    • Calculate equation of the regression line
      • y-hat = b1*x + bo
        • b1 = “slope” of the line
        • b0 = “y-intercept”
      • b1 = SSxy/SSxx
      • b0 = (∑y/n) – b1*(∑x/n)
    • Examples
      • Beer party data: {(60,10), (70,12), (80,20), (90,40)}
      • Calculate slope (b1) and y-intercept (b0) for linear equation
      • Solve for each “x” value (i.e., plug in 60, 70…and solve for y) to produce corresponding “y-hat” values

Activity:

  • Calculate Linear Regression Equations
    • Use calculations from previous class
      • Data set 1: {(3,5), (5,8), (8,11), (12,10)}
      • Data set 2: {(50,12), (60,15), (70,20), (80,30)}
      • Data set 3: {(2,12), (4,9), (7,6), (11,3)}
  • Use linear equations to calculate “y-hat” values
    • Add a new column to each data table for “y-hat” values

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