8 1 linear regression
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8.1 Linear Regression. Lesson Obj : IWBAT find the equation of a line that best fits a set of data. Guiding Question: How can we model data linearly?. Linear Function: Either Or m = slope, b is y-intercept.

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8.1 Linear Regression

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8 1 linear regression

8.1 Linear Regression

Lesson Obj: IWBAT find the equation of a line that best fits a set of data.


Guiding question how can we model data linearly

Guiding Question: How can we model data linearly?

  • Linear Function:

    Either

    Or

    m = slope, b is y-intercept

  • Linear Regression: find an equation that is the best fit for the set of given data.

  • (Think Scatterplots)


Guiding question how can we model data linearly1

Guiding Question: How can we model data linearly?

  • This line seems to be a best fit. Put the points into a table and write the equation of the line.

  • Be as accurate as possible.


Guiding question how can we model data linearly2

Guiding Question: How can we model data linearly?

Table of Points.

Linear Equation

Is this as accurate as we can be?


Guiding question how can we model data linearly3

Guiding Question: How can we model data linearly?

Notice that there are places where there is space between the line and points.

How can we use that to better our linear function?

The distance between the actual points and the line are called residuals and are found by subtracting what the equation gives from the actual value.


Guiding question how can we model data linearly4

Guiding Question: How can we model data linearly?

  • Find the sum of the squares of the residuals


Guiding question how can we model data linearly5

Guiding Question: How can we model data linearly?

  • Assignment: Pg. 353 1-3


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