A sample is a subset of the population.
The sample is a subset of the population.
The formula for calculating the standard error (or some call it the standard deviation) is almost the same as for the population; except the denominator in the equation is n-1, not N (n = number in your sample, N = number in population). See the formulas in the related link.
A representative sample is one where the statistics of the sample are the same as the statistics for the parent population.
It can be.
A sample consists of a small portion of data when a population is taken from a large amount.
The population consists of every possible unit where a sample is a subset of the population. Note that population and sample need not refer to persons. For example, if studying biodiversity, the population could consist of plots of land.
Sample. A random sample ensures that everyone or thing has a proportionally equal chance of being picked. The idea is that the sample should be representative of the whole population.
A representative sample accurately reflects the characteristics of the population it is drawn from. This means that the sample is chosen in a way that each member of the population has an equal chance of being included in the sample, which helps to ensure that the findings can be generalized back to the population.
Random Selection Process
A Sample
A sample is a subset of the population.
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.
A sample is a subset of the population.
The sample is a subset of the population.
Data is neither sample nor population. Data are collected for attributes. These can be for a sample or a population.
Sometimes a population consists of a number of subsets (strata) such that members within any particular strata are alike while difference between strata are more than simply random variations. In such a case, the population can be split up into strata. Then a stratified random sample consists of simple random samples, with the same sampling proportion, taken within each stratum.