Examples of population in the following topics:

 A statistical population is a set of entities from which statistical inferences are to be drawn, often based on a random sample taken from the population.
 Since in this case and many others it is impossible to observe the entire statistical population, due to time constraints, constraints of geographical accessibility, and constraints on the researcher's resources, a researcher would instead observe a statistical sample from the population in order to attempt to learn something about the population as a whole.
 This type of information gathering over a whole population is called a census .
 If different subpopulations have different properties, so that the overall population is heterogeneous, the properties and responses of the overall population can often be better understood if the population is first separated into distinct subpopulations.
 For instance, a particular medicine may have different effects on different subpopulations, and these effects may be obscured or dismissed if such special subpopulations are not identified and examined in isolation.




 A OneWay ANOVA hypothesis test determines if several population means are equal.

 Your data should be a simple random sample that comes from a population that is approximately normally distributed.
 You use the sample standard deviation to approximate the population standard deviation.
 When you perform a hypothesis test of a single population mean µ using a normal distribution (often called a ztest), you take a simple random sample from the population.
 The population you are testing is normally distributed or your sample size is sufﬁciently large.
 When you perform a hypothesis test of a single population proportion p, you take a simple random sample from the population.

 In order to estimate a population proportion of some attribute, it is helpful to rely on the proportions observed within a sample of the population.
 This leads to an estimate of 52% as A's support in the population.
 The population proportion, p, is estimated using the sample proportion $\hat{p}$.
 Therefore, a good population proportion for this example would be 0.52$\pm$0.2498.

 Independent groups mean that the two samples taken are independent, that is, sample values selected from one population are not related in any way to sample values selected from the other population.
 The parameter tested using matched pairs is the population mean (see ).
 The parameters tested using independent groups are either population means or population proportions.
 This image shows a series of histograms for a large number of sample means taken from a population.
 In this section, we explore hypothesis testing of two independent population means (and proportions) and also tests for paired samples of population means.

 Perform tests of a population mean using a normal distribution or a student'st distribution.
 (Remember, use a student'st distribution when the population standard deviation is unknown and the distribution of the sample mean is approximately normal.
 ) In this chapter we perform tests of a population proportion using a normal distribution (usually n is large or the sample size is large).
 If you are testing a single population mean, the distribution for the test is for means:
 If you are testing a single population proportion, the distribution for the test is for proportions or percentages:
