# Definition of Population and Examples

Infodasar.com-In the statistics, the population is the whole set of where the sample statistics are taken. Populations can refer to a whole group of people, objects, events, hospital visits, or measurements. Thus, the population can be said as an aggregate observation of subjects grouped together by common features.

## Definition of Population

Unlike samples, when conducting statistical analyses on the population, there is no standard error to be reported that is because the error informs analysts using a sample how far their estimate might deviate from the value The actual population. But since you are working with the actual population, you already know the true value.

## Population Basics

The population can be defined by a number of characteristics in a group that statisticians use to draw conclusions about the subject in a study. A population can be unclear or specific. Examples of populations (vaguely defined) include the number of newborns in North America, the total number of technology startups in Asia, the average height of all the world's CFA exam candidates, the average U.S. taxpayer weight, and so on. Populations can also be defined more specifically, such as the number of newborns in North America with brown eyes, the number of startups in Asia that failed in less than three years, the average height of all women's CFA exam candidates, the average weight All U.S. taxpayers are over 30 years old, among others.
Oftentimes, statisticians and researchers want to know the characteristics of each entity in a population, so it can draw the most appropriate conclusions. However, this is not possible or cumbersome because the population number tends to be quite large.
For example, if a company wants to know if each of its 50,000 customers served during the year is satisfied, it may be difficult, costly and impractical to call each client on the phone to conduct a survey. Because the characteristics of any individual in a population cannot be measured due to time constraints, resources, and accessibility, population samples are taken.

## Population Samples

Samples are a random selection of population members. This is a smaller group taken from a population that has the characteristics of the entire population. Observations and conclusions made to the sample data are associated with the population.
Information obtained from statistical samples allows statisticians to develop hypotheses about larger populations. In statistical equations, the population is usually denoted by uppercase N while the sample is usually denoted by lowercase letters.

## Population Parameters

Parameters are data based on the entire population. Statistics such as average and standard deviations, when taken from the population, are referred to as population parameters. The population's average population and standard deviation are represented by the Greek letter μ and σ.
Standard deviation is a variation in the population inferred from variations in samples. When the standard deviation is divided by the square root of the number of observations in the sample, the result is referred to as the average standard fault.
While parameters are population characteristics, statistics are characteristic of samples. Inferential statistics allow you to create educated forecasts about population parameters based on statistics calculated from samples taken randomly from that population.

## Real-World Population examples

As an example of a population in the real world, let's say the denim clothing manufacturer wants to check the quality of stitches on his blue jeans before sending it to a retail store. It is not cost-effective to inspect every pair of manufactured blue jeans manufacturer (population). Instead, the manufacturer sees only 50 pairs (samples) To draw conclusions about whether the entire population is likely to be stitched properly.