Sometimes they do, sometimes they don't.
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It is the number of units in a statistical study. The "population" need not refer to people. For example, when researching house prices in an area, the population would comprise all the houses in the area and the population size would be the number of houses.
First you have chose an estimator for what you want to know about the population. In general the level of variability in the result that any estimator provides will depend on the variability in the population. Therefore, the greater the variability in the population the larger your sample size must be. You will also need to decide how much precision is required in your estimate. The more precision you require the greater your sample size will have to be.
Statistics often requires one to make estimates of some measure (variable) about a set of units. The total number of such units is the population size. Note that population, in this context, need not refer to people. If the study is about household expenditure on food (in some area), then the population is all households and the population size is the number of households (in that area). If the study is about diversity of insects in a field, the population may be all 1-metre squares in the field, and the size of the population will be the number of such plots - which will equal the area of the field.
No, more information is needed to determine the margin of error. For example, one may need to know the sample's mean, the sample size, and the standard deviations of the population and sample. Depending on the type of test one is performing, certain parameters need not be known. For example, the population standard deviation does not need to be known in a one sample T-test.
You can estimate a population's size when counting individuals if the density in a sample is greater than the population density.