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15 Cards in this Set

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