Based on Sampling and Sampling Distributions: Data analysis plays an important r

Question

Based on Sampling and Sampling Distributions:

Data analysis plays an important role in business making decisions. In many situations, we want to make inferences that are based on statistics calculated from sample data to estimate the values of population parameters.   For example, a pollster may be in interested in the sample results as a way of estimating the actual proportion of votes that each candidate will receive from a population of voters. In a business setting, do you think it is important to understand the population in which your samples are drawn? If so, why or why not? Are there situations where you feel that sample data is not a true representation of the population?

Explanation / Answer

It is important to understand the population from which the samples are drawn. Since, the term population is wide and cannot be counted rigorously, therefore, a clear definition of the population from which the samples are drawn has to be properly stated. For example, suppose, an analyst wnats to see if the new physiotherapy method has any effect on elderly paralytic patients. Now the population concerned is elderly paralytic patients, but who are elderly, and what level of paralysis do they have need to be understood. Precisely, a population of elderly people (55-65) and with paralysis level of 3 shoul be considered for the study. A samples should be drawn from this population.

Suppose, a sample data consists of 20 elderly people aged, 50-75 has been randomly chosen from a clinic of orthopaedic surgeon with paralysis level of 1-3 (where, 1 considers severe paralysis, 2 medium and 3 minor) are taken into account and regression analysis is performed, then the result would be wrong as the sample do not represent the population correctly.

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