diff --git a/education/statistics/5.html b/education/statistics/5.html index 976b1cf..3001d6f 100644 --- a/education/statistics/5.html +++ b/education/statistics/5.html @@ -2,7 +2,7 @@ title: 5 description: published: true -date: 2026-02-11T14:42:59.270Z +date: 2026-02-11T14:43:25.309Z tags: editor: ckeditor dateCreated: 2026-02-11T14:42:59.270Z @@ -65,18 +65,18 @@ dateCreated: 2026-02-11T14:42:59.270Z

Ra2 will always be smaller than R2.

 

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Assumptions

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Linearity

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Assumptions

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Linearity

The relationship between the explanatory X and the response variable Y should be linear.

Methods for fitting a model to non-linear relationships exist but are beyond the scope of this course.

Check using a scatterplot of the data, or a residuals plot.

 

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Nearly Normal Residuals

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Nearly Normal Residuals

The residuals should be nearly normal.

This condition may not be satisfied when there are unusual observations that do not follow the trend of the rest of the data.

Check using histogram or normal probability plot of residuals.

 

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Constant variability

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Constant variability

The variability of points around the least squares line should be roughly constant.

This implies that the variability of residuals around the 0 line should be roughly constant as well.

It is also called homoscedasticity.