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The population consists of every possible unit where a sample is a subset of the population. Note that population and sample need not refer to persons. For example, if studying biodiversity, the population could consist of plots of land.
Yes. You could have a biased sample. Its distribution would not necessarily match the distribution of the parent population.
A probability sample is one in which each member of the population has the same probability of being included. An alternative and equivalent definition is that it is a sample such that the probability of selecting that particular sample is the same for all samples of that size which could be drawn from the population.
If I take 10 items (a small sample) from a population and calculate the standard deviation, then I take 100 items (larger sample), and calculate the standard deviation, how will my statistics change? The smaller sample could have a higher, lower or about equal the standard deviation of the larger sample. It's also possible that the smaller sample could be, by chance, closer to the standard deviation of the population. However, A properly taken larger sample will, in general, be a more reliable estimate of the standard deviation of the population than a smaller one. There are mathematical equations to show this, that in the long run, larger samples provide better estimates. This is generally but not always true. If your population is changing as you are collecting data, then a very large sample may not be representative as it takes time to collect.
A standard deviation for a sample makes a judgment on the whole data set whereas the population standard deviation uses the shole data set. If the questions says for example, a sample of 50 peoples height was taken... you would use the sample method but if you were asked : "Everyone in the class had their height measured" you could use the population method Hope that helps