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Gathering data is the first step in statistical analysis
Gathering data is the first step in statistical analysis.
Say for example that you want to know something about all the people in France.
The population is then all of the people in France.
It is too much effort to gather information about all of the members of a population (e.g. all 67+ million people living in France). It is often much easier to collect a smaller group of that population and analyze that. This is called a sample.
A representative sample
The sample needs to be similar to the whole population of France. It should have the same characteristics as the population. If you only include people named Jacques living in Paris who are 48 years old, the sample will not be similar to the whole population.
So for a good sample, you will need people from all over France, with different ages, professions, and so on.
If the members of the sample have similar characteristics (like age, profession, etc.) to the whole population of France, we say that the sample is representative of the population.
A good representative sample is crucial for statistical methods.
Note: Data from a proper sample is often just as good data from the whole population, as long as it is representative!
A good sample allows you to make accurate conclusions about the whole population.