sample.
Population
differences between quantitative and qualitative data
Selecting individuals at random- *apex
AnswerA sample is a subset of a population. Usually it is impossible to test an entire population so tests are done on a sample of that population. These samples can be selected so that they are representative of the population in which cases the sample will have weights, strata, and clusters. But usually people use random samples. So it's not that the line is different, it's that the line comes from different data. In stats we have formulas that allow a sample to represent a population, if you have the entire population (again unlikely), you wouldn't need to use this sample formulas, only the population formulas.
You are studying the sample because you want to find out information about the whole population. If the sample you have drawn from the population does not represent the population, you will find out about the sample but will not find out about the population.
sample
at random to represent the population
A small number of people used to represent an entire population is called a sample. Typically the sample reflects characteristics of the larger population from which it is drawn.
A biased sample is a sample that is not random. A biased sample will skew the research because the sample does not represent the population.
A biased sample is a sample that is not random. A biased sample will skew the research because the sample does not represent the population.
The sample must be large and random.
A sample must be representative, meaning that it reflects the characteristics of the population it is drawn from. It must also be large enough to minimize sampling error and increase the likelihood of capturing the population's diversity.
The use of a small number of people to represent a greater population is called sampling. The sample can be randomly chosen so that it is a reliable reflection of most of the population.
Bias
a sample
sample.