Difference Between Population and Sample
Population vs Sample
The word “population” simply means the body or the total number of inhabitants of the same species in a place or territory, whether it’s a country, city, state, or any area or district. It could also mean or pertain to a particular race or class. An example of this is the native population and the student population. Populations can either be small or large depending mostly on the geographical area that you are focusing on. In statistics, however, it gives us a slightly different meaning for the word “population.” In statistics it may refer to individuals that are not necessarily animate. It is the group of data, individuals, specimen, or items from which you are to get your information for your statistical study. Population is also sometimes called “universe.” It is the full or entire collection to be analyzed or studied. It holds the total subject of interest.
A sample is a small portion or part taken from something whether it’s a particular race, inhabitants, data, or items to show or to be the representative of the whole. Its significance to statistics is fairly similar to its original meaning. In statistics, a sample represents a portion of the population you are going to test or study. In other words, it is a subset of the population. It is a slice of it and all of its characteristics. A sample should be randomly drawn so that there are no biases and you will be sure that your sample covers all the characteristics of your chosen population otherwise your result is invalid. In short, we can simply say that every individual of the sample that you have taken is a member of your target population. It is helpful to get samples because it is difficult to study and obtain your needed information from the entire whole.
Here are some advantages why we gather samples instead of surveying or studying the whole population. First of all, in researching and gathering your information, it would be costly and very impractical to actually be working on the whole rather than just having random samples. Always keep in mind that samples also possess the characteristics of the population. You don’t need to survey everyone just to get the idea of their qualities. Secondly, it saves time to just focus on your sample. It would take a long time to survey, gather information, and analyze the results from the population as a whole. Because of it being time consuming and having a lot of data to analyze, the possibility of committing errors are higher. You have a bunch of data that you might over look. Comparing samples from the population, samples are more controllable and easier to handle and study. Always be sure that your sample is randomly taken so that you will have a better view of the qualities or information that you are looking for in the population.
1.When you are talking about the population, it is pertaining to the whole. A sample is a part of the population that you randomly choose to represent the whole.
2.Every member of your sample belongs to the population. Meaning every individual in your sample bears the characteristics of the population.
3.To have more accurate results in your study, you must choose your sample randomly and without any biases.
4.Conducting a survey or study to the whole population has a greater possibility of having erroneous results than having to study only your controlled sample.
5.The population bears the whole subject of interest while the sample is just a part of the subject of interest.
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