Estimating Population Parameters

Estimating Population Parameters
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A population consists of all possible individuals, objects, or observations a researcher is interested in studying. A population parameter summarizes characteristics such as dispersion and location of the population. Population parameters are assumed to be fixed or take only one value. Examples include population proportion, standard deviation (σ), and the population mean. The primary objective of quantitative research is to find out the characteristics of populations by estimating parameters. In practice, it is impossible to find the true value of population parameters since they belong to populations. It is almost impossible, unfeasible, or time-consuming to gather data from the entire population. Instead, researchers collect data from samples and use the sample data to make educated guesses or estimate the population parameters (Hahs-Vaughn & Lomax, 2020). Some examples of population parameters that cannot be calculated but can be estimated include the percentage of married adults in the US, the mean systolic pressure of all adults in the US, and the proportion of all college students above 50 years in the US.
A sample statistic such as the sample mean can be used to estimate a population parameter such as the population mean. Since we are using a sample and not the entire population, the sample statistic will likely not be equal to the population parameter we are estimating, resulting in some errors. A standard error shows how variable a statistic is if an experiment is repeated several times. It indicates the amount of precision around the estimate of a parameter. A large standard error indicates that the statistic varies by a significant amount; a small standard error indicates that it onl...