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random sample

Q: A sample in which each individual or object in the entire population has an equal chance of being selected?

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Usually, we make a distinction between a population and a sample. The population is the entire set of values or attributes of interest while the sample is a subset of the population.

Preindustrial society

== == In 2008, population of Tehran is roughly 8 million Don't know Tehran, but in the year 2000 the entire population of Iran was 70,351,549

The total population of Sterling Heights, MI is 124,471 people. The Latino population is 1.34 percent of that or 1,665 people. This is a low percentage when compared to the 12% of the entire US.

just over 677 million standard tons (mean average)

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Sample-a small group selected by researchers to represent the most important characteristics of an entire population. (according to my book)

Usually we are interested in the characteristics of large populations of items or people. It would often prove costly or impossible to measure these characteristics for the entire population. We therefore measure them for a carefully selected sample of the population and attempt to make scientific inferences about the entire population from the characteristics of the sample.

Almost the size of Michael Moore.

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".

The entire House of Representatives

The entire 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.

More people live in Dublin than in any other individual part of Ireland, but the entire population outside of Dublin would be bigger than Dublin's population.

In (Simple) random sampling, all of the units in the sample have the same chance of being included in the sample. Units are selected randomly from a population by some random method that gives equal probability to each element. In stratified random sampling, the entire population is divided into heterogeneous sub-popuation known as strata (sub-population with unequal variances) and a random sample is chosen from each of these stratum. The reason when to use which depends on the situation and need of the experimenter.

This is a very vague area for new students in Statistics, especially for non-math students.Random Sample: Each member of the entire population has an equal chance of being selected.Simple Random Sample: You can select groups of size n from the entire population, and every possible group has the same chance of being selected.Example: Consider a box with 100 marbles.Random Sample: Reach in and select one marble. Each marble has the same chance of being selected.Simple Random Sample: Reach in and select marbles in groups of 6 (n = 6). No matter how many times you do this, every possible group of six marbles has the same chance of being selected. If you then try selecting groups of 17 (n = 17) marbles, you will also find that every possible group of 17 marbles has an equal chance of being selected.Random, but not Simple Random: For the Presidential Election, lets say you select a random sample of all voting precincts in your state, then interview *all the voters as they leave the polling place. The sample is random because all precincts have an equal chance of being selected. The sample is not simple random, because those voters from precincts that were *not* selected have no chance of being interviewed. This is also known as a Cluster Sample.There is no such thing as a sample that is "Simple Random, but not Random" because n can also equal a sample of size 1.

The entire group that the researcher is interested in is called the population or the target population.

yes