Population vs. Sample
Difference Between Population and Sample
Population is the word that only means the total population of the same type species of humans in a country or region. A particular race or class may be concerned. An example is the indigenous population and student population. Groups can be either be small or large for most of the territory that you focus on. In statistics, it can refer to people who do not necessarily move. There is a group of data, individuals, test, or things you will learn about the statistical study.
A sample is a small part or parts of something, whether it is a special race, people, documents or objects to appear or be represented as a whole. The significance of the statistics are quite similar to the original meaning. The figures represent a sample of the population to test or study. In other words, there is a subset of the population. It is a slice of it and all of its assets. Samples should be randomly chosen so that there is no bias, and you want to make sure that the sample contains all the features selected population as a whole. It can be useful if we have a sample because it can be extremely difficult to analyze entire population as a whole.
Here are some benefits for each of the pooled sample, instead of surveying and studying the entire population.
Always remember that the sample also possesses qualities of certain parts of population. You do not need to identify all just to get an idea of their properties. Second, it saves time to just focus on the sample. It would take a long time to find, collect and analyze data from the population as a whole. Because it is time taking and has a lot of data to analyze, the risk of error is greater. Sampled are more manageable and easier to handle and learn. Always ensure that the sample is taken at random, so you will have a better overview of the features or information you are looking for in the population
1 When you talk about population, its for all. Sample is part of the population selected at random to represent the whole.
2. Every member belongs to a sample of the population. Meaning each individual in the sample is the characteristics of the population.
3. To have detailed results of your research, you must select samples at random and without bias.
4. Conducting survey or study of the entire population is more likely to get errors.
5. The population is all a matter of interest, but the sample is only part of the material of interest.