How do you minimize the value of the error or uncertainty when fitting sample data?
Statisticians use least square fitting to ensure that they have optimized their sample data in the fitted model. When they do so, they are able to minimize the value of the statistical error/uncertainty. The least square fitting model can either be linear or non-linear.
The statistical error or uncertainty is described by the following equation;
Where,
ε is the statistical error or uncertainty
y is the dependent variable from the data set
f is the fitted function to the sample data set
n is the number of observations in the sample data set
Follow these steps to come up with the least square estimators of the parameters in the fitted linear model:
Sign up for free and get instant discount of 12% on your first order
Coupon: SHD12FIRST