Real life example for linear regression: drug dosage and blood pressure of patients




Medical researchers often use linear regression to understand the relationship between drug dosage and blood pressure of patients.

For example, researchers might administer various dosages of a certain drug to patients and observe how their blood pressure responds. They might fit a simple linear regression model using dosage as the predictor variable and blood pressure as the response variable. The regression model would take the following form:

blood pressure = β0 + β1(dosage)

The coefficient β0 would represent the expected blood pressure when dosage is zero.

The coefficient β1 would represent the average change in  blood pressure when dosage is increased by one unit.

If β1 is negative, it would mean that an increase in dosage is associated with a decrease in blood pressure.

If β1 is close to zero, it would mean that an increase in dosage is associated with no change in blood pressure.

If β1 is positive, it would mean that an increase in dosage is associated with an increase in blood pressure.

Depending on the value of β1, researchers may decide to change the dosage given to a patient.

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