Representativeness refers to the degree to which a particular sample, group, or population accurately represents the characteristics of a larger group, population or universe. This concept is fundamental in statistics, data analysis and research, and it plays a vital role in generating reliable and valid conclusions from data.
A sample is considered representative when the characteristics of the sample reflect the characteristics of the larger population from which it is drawn. For example, if a sample of 1000 people is taken from a population of 10,000 people, the sample will be considered representative if the characteristics of age, gender, race, income, and other relevant factors of the sample resemble the population as a whole.
Representativeness is important in many fields including marketing, polling, politics, economics, social sciences, and more. Ensuring that a sample is representative of a larger population is crucial to drawing accurate conclusions from data and making informed decisions. Often, random sampling techniques or other methods of stratification are used to ensure that a sample is representative.
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