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15 Cards in this Set
- Front
- Back
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Population?
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Everybody you want information about (described generally.)
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Individuals?
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Each member of the population (can be people, animals or things.)
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Variable?
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is any characteristic of an individual.
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Sample?
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“subset of individuals” you actually measure.
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Sampling Frame?
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“List of individuals” who could possibly be in your sample
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Confounding Variables?
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something other then what you are trying to study that makes the GROUPS (not individuals) different. Confounding variables make it impossible to draw a conclusion.
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Variability?
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Describes how spread out the variables of the sample statistic is. Answers are scattered. Increasing the sample size does address variability.
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Proportion?
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How to calculate proportion:
# Of Yes’s divided by the total sample size. A proportion is a decimal b/w zero and one. |
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Bias?
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Favors a certain outcome. Increasing the sample size does not fix the bias.
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Example of sampling error?
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You made the mistake when picking thing people.
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Example of Non-sampling error?
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biased questions, recording errors, math errors, anything other then picking the wrong people.
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Simple Random?
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picking names out of a hat, everyone has a fair chance.
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Stratified Sample?
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break population down into groups then do a SRS from each group, this way each group is represented.
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Parameter?
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What you are trying to find out. Usually describes the population.
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Statistic?
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The value from your sample, used to estimate the parameter.
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