Why is it necessary to have the number of independent variables less than the number of data points in a regression setup? If suppose, it is the other way round, i.e. the number of independent variables far exceed the number of observations, then what should be the way out?


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Consider one of the simplest possible case. One independent variable (so 2 parameters, including the constant). One data point.

Plot your one data point

Draw a straight line through that one point. Draw a different straight line through the same point. Draw a third one. ... and so on.

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They all fit the data perfectly. Which one are you going to pick?

The problem is similar with two points and two predictors (with a plane through two points it's a bit like trying to rest a sheet of plywood on top of a picket fence - stable in one direction, but it's a see-saw in the other).


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