What Is a Population?

Population is a statistical term that designates the pool from which a sample is drawn for a s🅠tudy. Any selection grouped by a common feature can be considered a population. A sample is✱ a statistically significant portion of a population.

Understanding Populations

Statisticians, scientists, and analysts prefer to know 𓆏the characteristics of every entity in a population to draw the most precﷺise conclusions possible. This is impossible or impractical most of the time, however, because population sets tend to be quite large.

A sample of a population must usually be taken because the characteristics of every individual in a population can't be measured due to constraints of time, resources, and accessibility.

There's no real way to gather data on all the great white sharks in the ocean, which is a population. Finding and tagging each one isn't feasible. Marine biologists instead tag the great whites they can as a sample. They begin collecting information on them to make inferences about the entire population of great whites. This is a random sampling approach becausಌe the initial encounters with tagg🎃ed great whites are entirely random.

A valid statistic can be drawn from either a sample or a study of an entire population. The objective of a random sample is to avoid bias in the results. A sample is random when every entity in an entire population has an equal chance to be selected to participate.

How to Measure a Population

The difficulty in measuring a population lies in whatever you're attempting to analyze and what you're trying to accomplish. Data must be collected through surveys, measurements, observation, or other methods. Gathering the data on a large population generally isn't done because of the costs, time, and resources required to obtain it.

For example, imagine you hear in an ad, "62% of doctors recommend XYZ for their patients!" All doctors with patients who could use Drug XYZ in the U.S. likely weren't contacted to confirm this claim. Instead, 62% of the doctors who responded to the several hundred or thousands of surveys sent out said that they would recommend XYZ. This is a population sample.

Population and Investing

A parameter is a characteristic of a population. A statistic is a characteristic of a sample and samples can only result in inferences about a population characteristic. Inferential statistics allow you to make an educated guess about a population parameter based on a statistic computed from a sample randomly drawn from that population.

Statistics such as averages or means and 澳洲幸运5官方开奖结果体彩网:standard deviations are referred to as population parame🐟ters when they're taken from populations. Many, such as a population's mean and standard deviation, are represented by Greek letters like µ (mu) and σ (sigma). These statistics are inferential in nature, much of the time because samples are used rather than populations.

Market and investment analysts use statistics to analyze investment data and make inferences about the marke🔯t, a specific investment, or an index. Financial aꦓnalysts can evaluate an entire population in some cases because price data has been recorded for decades. The price of every publicly traded stock could be analyzed for a total market evaluation because the prices are recorded. This is a population in terms of investment analysis.

▨An analyst can calculate parameters with all this data, but the parameters used by analys🌞ts are only occasionally used in the same way that statisticians and scientists use them.

Some of the parameters you might💃 see used by investment analysts, statisticians, and scientists, and their differences are:

The Bottom Line

A population is the statistical pool being studied from which data is extracted. Populations can be difficult to gather data on, especially if the studied topic is expansive and widely dispersed. Studying humans is an excellent example. There's no way to gather data on every brown-eyed person in the world, so random sampling is the only way to infer anything about that population.

Populations in investment analysis are generally s👍pecific types of assets bein🔯g analyzed. These data sets are generally small in statistical terms and easy to acquire because they've been recorded, unlike data on living organisms, which is much more difficult to obtain.