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For more information, please see full course syllabus of Statistics
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Lecture Comments (4)

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Post by Sarawut Chaiyadech on August 14, 2013

sum of x squared= 1764?

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Post by Nick Lardner on June 8, 2012

Ey int the first extra example is 554.15 not 554.18. not a big deal but just thought you guys should know

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Last reply by: Alex Moon
Sun Nov 11, 2012 12:42 AM

Post by Julia Mai on October 9, 2011

This is not a very good lecture on regression. On the AP exam, we are not required to calculate regression...we have to interpret it. I would like to see more examples on application. We can use the calculator to find the r-value for us.

Least Squares Regression

  • The least-squares regression line is the best fitting line to bivariate data. An independent variable is used to “predict” a value of a dependent value.

  • By investigating the residuals, the difference between the predicted and actual value of the dependent variable, is used as a diagnostic check on the model.

  • Data can be transformed in order for the residuals to look like they come from a normal distribution.

Least Squares Regression

Lecture Slides are screen-captured images of important points in the lecture. Students can download and print out these lecture slide images to do practice problems as well as take notes while watching the lecture.

  • Intro 0:00
  • Least Squares Regression Line 0:06
    • Why Least Squares?
    • Equations
  • Example 1: Age and Price 2:02
  • Example 2: Weld Diameter 5:47
  • Diagnostics 8:39
    • Residuals
    • Normal Probability Plot
    • Studentized Residuals (Hat Matrix)
  • Transformations 10:48
    • Logarithmic Transformation
    • Square Root Transformation
  • Extra Example 1
  • Extra Example 2