1.2 Sampling LEARNING GOAL

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Presentation transcript:

1.2 Sampling LEARNING GOAL Understand the importance of choosing a representative sample and become familiar with several common methods of sampling. Page 11

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. Page 11-12

Definition of Bias A statistical study suffers from ____________if its design or conduct tends to favor certain results. Page 12

Sampling Methods

Simple Random Sampling: Every sample of the same size has an equal chance of being selected. Computers are often used to generate random numbers. Page 17 Slide 1.2- 5

Convenience Sampling: We use a sample that happens to be convenient to select. Use results that are readily available. Page 17 Slide 1.2- 6

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. Page 17 Slide 1.2- 7

Cluster Sampling: Divide the population into clusters, randomly select some of those clusters, then choose all members of the selected clusters. Page 17 Slide 1.2- 8

Stratified Sampling: Partition the population into at least two strata, then draw a sample from each. Page 17 Slide 1.2- 9

Methods of Sampling

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. Page 16 Slide 1.2- 11