Population parameters or population characteristics can be estimated by taking representative samples of a population

Population parameters or population characteristics can be estimated by taking representative samples of a population. In other words, conclusions about an entire population can be inferred from a sampling of that population. This sampling of the population can then be examined, and inferences made about the general population it represents. Various measures provide different types of data or measurements of data from which conclusions can be derived. Examples of these measures are Measures of Central Tendency and Measures of Dispersion.

Address one of the following prompts in a brief but thorough manner.

• What are the most common measures of central tendency? 
• What information is provided by each of these measures and what do they tell us? How could you use measures of central tendency in decision-making as a leader and manager?
• What are the various measures of dispersion?
• What are the uses of these measures and what are their limitations?
• What does each of these measures tell a researcher? A leader or manager?

Your posting should be approximately 500 words in length.

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Population parameters or population characteristics can be estimated by taking representative samples of a population

Introduction

The world is full of people, animals, plants and other organisms. They live in different places at different times and their characteristics can be very different from one another. For example, some people are tall and others are short; some people have blue eyes while others have brown eyes—and so on! To get an accurate picture of all these different types of humans (or any other kind of living thing), we must sample them from our population as accurately as possible.

A sample is a subset of the original population.

A sample is a subset of the original population.

A sample is a subset of the original population, but it is not the original population.

The term “sample” refers to any subset that represents only part of an entire set.

A representative sample can be sampled with equal probability from an entire population.

A representative sample can be sampled with equal probability from an entire population. A representative sample is a random sample.

The term “random” means that all members of the population have an equal chance of being selected for inclusion in this particular group or treatment group. In other words, it’s not based on some predetermined factor like race or gender; instead it’s determined randomly through simple mathematics (see below).

The more people in the sample, the better the accuracy and precision of estimates.

The more people in your sample, the better the accuracy and precision of estimates.

For example, if you want to estimate the average number of people who live in an area or country, then it’s better to use a sample that represents all known residents (e.g., everyone living in town) than one that only contains those who live on one side of town (e.g., only those with addresses on Main Street).

In general, smaller samples are more precise because they represent larger proportions of the population.

In general, smaller samples are more precise because they represent larger proportions of the population. For example, if you were to take a sample of 100 people from your office and ask them how many days they work in a year, you would probably get quite different answers than if you were to ask 10 people instead.

Other factors that can affect precision include:

• Cost – A smaller sample size will generally cost less than one with a bigger number; however, this does not always hold true (for example, some studies require expensive equipment).
• Time – It takes longer for someone who has never done an experiment before to learn how to do one properly than it does for someone who has already done hundreds of such experiments; therefore it may be worth considering whether your time is worth more than $20 per hour (or whatever) when calculating costs versus results from more sophisticated statistical methods like ANOVA or t-tests

More accurate and precise data can be collected by taking more samples in different places and times than with a single large random sample.

In order to obtain more accurate and precise data, it is important that a representative sample be taken from the population. The size of this representative group depends on how much variation there is in the characteristics of those individuals; larger samples will generally provide higher accuracy and precision than smaller ones.

Sample size can be expressed as:

• N = number of people/observations; or
• SS = standard error of estimate(SE).

Surveys are often used to collect data on populations that are not readily accessible, such as domestic animals or businesses.

Surveys are often used to collect data on populations that are not readily accessible, such as domestic animals or businesses. Surveys can be used to collect data on populations that are not readily accessible, such as domestic animals or businesses. These surveys typically involve asking people questions about their lives and experiences in order to gain insight into the lives of others.

The larger the number of observations taken, the greater your knowledge about the population you are working with

The larger the number of observations taken, the greater your knowledge about the population you are working with. The more people you sample and interview, the more accurate and precise your data will be. The larger sample size also increases your chances of getting representative information from each individual or group in society.

Conclusion

The next time you are working with data, think about how many samples it would take to get the best results. It may seem like a lot of work at first, but it will pay off in the long run.

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