Real life example for linear regression: fertiliser, water and crop yields

 



Agricultural scientists often use linear regression to measure the effect of fertilizer and water on crop yields.

For example, scientists might use different amounts of fertilizer and water on different fields and see how it affects crop yield. They might fit a multiple linear regression model using fertilizer and water as the predictor variables and crop yield as the response variable. The regression model would take the following form:

crop yield = β0 + β1(amount of fertilizer) + β2(amount of water)

The coefficient β0 would represent the expected crop yield with no fertilizer or water.

The coefficient β1 would represent the average change in crop yield when fertilizer is increased by one unit, assuming the amount of water remains unchanged.

The coefficient β2 would represent the average change in crop yield when water is increased by one unit, assuming the amount of fertilizer remains unchanged.

Depending on the values of β1 and β2, the scientists may change the amount of fertilizer and water used to maximize the crop yield.


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