1. 1.2 Sampling LEARNING GOAL
Understand the importance of choosing a representative sample and become familiar with several common methods of sampling.
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2. Definition Definition
A _____________is the collection of data from every member of a population.
Definition
A _________________is a sample in which the relevant characteristics of the sample members are generally the same as the characteristics of the population.
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3. Definition of Bias
A statistical study suffers from ____________if its design or conduct tends to favor certain results.
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4. Sampling Methods

5. Simple Random Sampling: Every sample of the same size has an equal chance of being selected. Computers are often used to generate random numbers.
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6. Convenience Sampling: We use a sample that happens to be convenient to select.
Use results that are readily available.
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7. Systematic Sampling:
We use a simple system to choose the sample, such as selecting every 10th or every 50th member of the population.
Select every kth member.
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8. Cluster Sampling: Divide the population into clusters, randomly select some of those clusters, then choose all members of the selected clusters.
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9. Stratified Sampling: Partition the population into at least two strata, then draw a sample from each.
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10. Methods of Sampling

11. Sampling Methods Keep in mind the following three key ideas:
A study can be successful only if the sample is representative of the population.
A biased sample is unlikely to be a representative sample.
Even a well-chosen sample may still turn out to be unrepresentative just because of bad luck in the actual drawing of the sample.
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