Multicollinearity
| Institution | University |
| Course | Mathematics |
| Year | 1st Year |
| Semester | Unknown |
| Posted By | Rose Oloo |
| File Type | |
| Pages | 25 Pages |
| File Size | 390.54 KB |
| Views | 11108 |
| Downloads | 87 |
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Description
A basic assumption is multiple linear regression model is that the rank of the matrix of observations on explanatory variables is the same as the number of explanatory variables. In other words, such a matrix is of full column rank. This, in turn, implies that all the explanatory variables are independent, i.e., there is no linear relationship among the explanatory variables. It is termed that the explanatory variables are
orthogonal.
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