Residual plots
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Residual Plots. 15.3. Residuals. The difference between actual data points and ones predicted by the regression line (line of best fit). If the residuals are small, the model is good. Predicted Value. Residual. Observed Value. Finding Residuals. From the graph.

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Residual Plots

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Residual plots

Residual Plots

15.3


Residuals

Residuals

  • The difference between actual data points and ones predicted by the regression line (line of best fit).

  • If the residuals are small, the model is good.

Predicted Value

Residual

Observed Value


Finding residuals

Finding Residuals

From the graph

From the equation (predicted outcomes)


Residual plots1

Residual Plots

  • Graph the x-value and the residual value to see how good our regression line models the data.

  • Look for 3 things for the model to be appropriate

    • Equal number of points above the x-axis and below

    • No obvious patterns (linear, exponential)

    • Small values for the residuals (y-axis)


What do these residual plots tell us

What do these Residual Plots tell us?

  • All of these show residual plots for bad models. What is the biggest problem with each of the graphs?

The top two graphs show residuals that are too large (too high on the y-axis)

The bottom two graphs show patterns which mean we shouldn’t use a linear model


Residual plot

Residual Plot

  • Does the Residual Plot indicate that our model (regression line) is a good predictor for this data? Explain.

  • YES

  • equal number of points above & below the x-axis

  • no pattern

  • all residuals ≤


Create a residual plot

Create a Residual Plot


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