Statistical Inference Was a Concept That Was Not Too Difficult

question 38

Essay

Statistical inference was a concept that was not too difficult to understand when using cross-sectional data. For example, it is obvious that a population mean is not the same as a sample mean (take weight of students at your college/university as an example). With a bit of thought, it also became clear that the sample mean had a distribution. This meant that there was uncertainty regarding the population mean given the sample information, and that you had to consider confidence intervals when making statements about the population mean. The same concept carried over into the two-dimensional analysis of a simple regression: knowing the height-weight relationship for a sample of students, for example, allowed you to make statements about the population height-weight relationship. In other words, it was easy to understand the relationship between a sample and a population in cross-sections. But what about time-series? Why should you be allowed to make statistical inference about some population, given a sample at hand (using quarterly data from 1962-2010, for example)? Write an essay explaining the relationship between a sample and a population when using time series.

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Definitions:

-dynia

A suffix used in medical terminology to indicate pain in a specified part of the body.

-itis

A suffix used in medical terminology to denote inflammation of an organ or tissue.

-lepsy

A suffix denoting a condition or form of seizure, such as in epilepsy.

Macula

A small central area in the retina of the eye that is responsible for sharp, detailed central vision.