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The sample regression function is a statistical approximation to the population regression function.
It all depends on what data set you're working with. There a quite a number of different regression analysis models that range the gambit of all functions you can think of. Obviously some are more useful than others. Logistic regression is extremely useful for population modelling because population growth follows a logistic curve. The final goal for any regression analysis is to have a mathematical function that most closely fits your data, so advantages and disadvantages depend entirely upon that.
1. PRF is based on population data as a whole, SRF is based on Sample data 2. We can draw only one PRF line from a given population. But we can Draw one SRF for one sample from that population. 3. PRF may exist only in our conception and imagination. 4. PRF curve or line is the locus of the conditional mean/ expectation of the independent variable Y for the fixed variable X in a sample data. SRF shows the estimated relation between dependent variable Y and explanatory variable X in a sample.
of, pertaining to, or determined by regression analysis: regression curve; regression equation. dictionary.com
the prefix of regression is regress