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16 Cards in this Set
- Front
- Back
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random variable
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Usually represented by a letter such as x, represents all the possible values of a specific characteristic we are interested in studying.
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variability
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Refers to the difference between subsequent values of the same random variable.
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model
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Used to represent a random variable and includes an equation that relates one or more influences. Explains the variability in the individual observations for that variable. These influences can be one or more other variables, such as controlled factors in an experiment or can be random error or noise in the process.
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model (example)
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X =
Where: x is a measured quantity is a constant is a random variable |
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population
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The overall group we are interested in drawing conclusions about.
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physical population
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Population is well defined and often finite group of items that are available at the time the study is conducted.
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conceptual population
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Population is either infinite or constantly changing.
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sample
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Subset of the population from which we collect info.
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population parameter
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A value that represents some trend in the overall population.
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population parameter (example)
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The population mean, a population proporiton.
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sample statistic
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A value calculated from the data (sample) that represents some trend. Is an estimate of the corresponding population parameter
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sample statistic (example)
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The mean calculated from the data.
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statistical inference
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Takes what is deduced from data or a study and applies it to the population.
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sampling error
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Represents the difference between the conclusions drawn from data and what actually happens in the population.
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retrospective study
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Based on historial data.
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retrospective study (advantage)
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Saves money because the product has already been produced and / or the data already exists.
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