The population is the set of all things which you wish to study. However, because collecting information from a large, possibly infinite, population is likely to be prohibitively large and time consuming, it is collected from only some members of the population. This subset is a sample.
The population may, but need not, consist of people. It could be the set of cars, or plots of land. There are a number of different ways of selecting samples: how the sample is selected will influence the quality of the statistics collected and, therefore, the validity of any conclusions.
A sample is a subset of the population.
A random sample is a sample (subset of the population) where each member of the population has an equal chance of being sampled. See related links.
n = sample sizen1 = sample 1 sizen2 = sample 2 size= sample meanμ0 = hypothesized population meanμ1 = population 1 meanμ2 = population 2 meanσ = population standard deviationσ2 = population variance
N is neither the sample or population mean. The letter N represents the population size while the small case letter n represents sample size. The symbol of sample mean is x̄ ,while the symbol for population mean is µ.
It means you can take a measure of the variance of the sample and expect that result to be consistent for the entire population, and the sample is a valid representation for/of the population and does not influence that measure of the population.
A Sample
Sampling is a method of selecting experimental units from a population so that we can make decision about the population. Sampling design is a design, or a working plan, that specifies the population frame,sample size, sample selection, and estimation method in detail. Objective of the sampling design is to know the characteristic of the population.
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.
It is not a sample. A sample must be a proper subset of the whole population.
A representative sample is one where the statistics of the sample are the same as the statistics for the parent population.
That the key characteristics of the population are reflected in the sample.
sample is the population we make our study about them.
From a sample of a population, the properties of the population can be inferred.