The sample consisted of the entire population.
The same basic formula is used to calculate the sample or population mean. The sample mean is x bar and the population mean is mu. Add all the values in the sample or population and divide by the number of data values.
Portion of the entire population used to estimate what is likely happening within a population.
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.
The sample is not a perfect representation of the population.
The population mean is the mean value of the entire population. Contrast this with sample mean, which is the mean value of a sample of the population.
The sample consisted of the entire population.
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.
The entire 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.
It is the population.
A random sample should be taken from an entire population.
The sample mean is an unbiased estimator of the population mean because the average of all the possible sample means of size n is equal to the population mean.
The same basic formula is used to calculate the sample or population mean. The sample mean is x bar and the population mean is mu. Add all the values in the sample or population and divide by the number of data values.
The best estimator of the population mean is the sample mean. It is unbiased and efficient, making it a reliable estimator when looking to estimate the population mean from a sample.
In maths, a sample is a group of things (people, books, pets etc...) randomly selected from a population (of people, books, pets etc...), which can be used to draw conclusions about the entire population. Sampling is very useful, since in most cases is it not possible to collect data from an entire population. Technically it is a "random subset of the population".
You calculate the actual sample mean, and from that number, you then estimate the probable mean (or the range) of the population from which that sample was drawn.