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Understanding Populations and Samples: Statistical Inferences

Learn about the difference between populations and samples, and how to generalize from a sample to a larger population. Explore selecting random samples carefully for valid inferences, types of samples, and the importance of unbiased sampling for accurate predictions.

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Understanding Populations and Samples: Statistical Inferences

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Presentation Transcript

  1. Warm Up 4/16

  2. Lesson 13: Populations and Samples Objective: • Students differentiate between a population and a sample. • Students investigate statistical questions that involve generalizing from a sample to a larger population.

  3. Populations vs. Samples • Population - A population is the entire set of objects (people, animals, plants, etc.) from which data might be collected. • Sample - A sample is a subset of the population.

  4. Fact There are many different ways to select a sample from a population. To make valid inferences about a population, you must choose a random sample very carefully so that it accurately represents the population.

  5. Types of Samples

  6. Fact • The results of an unbiased sample are proportional to the results of the population. So, you can use unbiased samples to make predictions about the population. • Biased samples are not representative of the population. So, you should not use them to make predictions about the population because the predictions may not be valid.

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