# ECON 3740 Lecture 5: Ch3a_03

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3 Dec 2017
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## Document Summary

If the population can be observed, there is no statistical problem: all the features if the population are known. The problem of statistical inference arises when the available information consists of a limited sample that is randomly drawn from the (possibly infinitely large) population and we want to infer something about the population using the sample at hand. Statistical estimation is one aspect of statistical inference1 - it concerns the estimation of population parameters such as the population mean and variance and the coefficients of a linear regression function. In chapter 2 the population regression function of y given x is defined as the conditional mean function of y given x, written as e(y | x). An important reason for our interest in this functional relationship is that it allows us predict y given values of x and to quantify the effect of a change in x on. Y (measured by say the derivative with respect to x. )