The answer depends on the variability of the characteristic that is being measured.
When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.
sample data drawn from one population is completely unrelated to the selection of sample data from the other 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.
Similarity: Both are counts of people/animals/things. Difference: Population is the total # of things, while sample is the # of things that you gather data on. If you pick the right sample size, you can be pretty confident that the results of the sample data is the same as the results of the entire population.
The sample size is the number of elements, out of a population, for which some data are measured in order to make assessments about the population.
Data is neither sample nor population. Data are collected for attributes. These can be for a sample or a population.
I would imagine that it is getting a representative sample number and a fraction of the population that does not have bias to the study in question
When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.
In reality, a statistician never really has ALL the data. The data is instead taken from a sample of the whole population. If this sample is representative of the entire population, then any statistics based on the sample should be good estimates of the whole but probably not a perfect match. Of course the more data you get from the whole population the better the estimate, but it will always be an estimate unless you census the enitire population.
sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
There are Goodness-of-Fit tests that can be used. The choice of test will depend on what is known about the population and sample data.
The data will most likely not be representative of the population as a whole and therefore be unreliable, and have the researchers making bad conclusions
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 must have a high probability of representing the population.
A sample consists of a small portion of data when a population is taken from a large amount.
The entire population.