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17 Cards in this Set
- Front
- Back
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Confounding |
occurs when the effects of two or more variables are related insuch a way that we need to take care in assigning the effect to one or to the other |
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Simple Random Sample |
gives every possible sample of given size the same chance tobe chosen. |
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Stratified Random Sample |
divides the population into groups of individuals that are sim-ilar in some way and then choose a separate SRS from each group. |
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Sampling Distribution |
describes how the statistic varies in repeated data production. |
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Parameter & Statistic |
A number that described a population is a and a () number that can be computed from the data is a () |
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Random Sampling |
To reduce bias, use |
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Variability |
To reduce the () of a statistic from an SRS, use a larger sample |
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Biased |
the design of a study is () if it favors certain outcomes |
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Comparative |
The best way to avoid confounding the effect of a treatment with lurking variables is todo a () experiment. |
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Randomization |
will creates treatment groups that are similar (except chancevariation) before the treatments are applied. |
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Repetition |
is used to reduce chance variation in the results. |
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Block |
is a group of experimental units that are known before theexperiment to be similar in some way that is expected to affect the response to thetreatments. |
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Explanatory variable |
Independent variable |
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Response Variable |
Dependent Variable |
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Regression line |
a line that describes how a response variable y changes as an explanatory variable x changes |
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Residual |
the difference between an an observed value of the response variable and the value predicted by the regression line |
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