Vocab Unit 6

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12 Terms

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Subsets
Groups within a larger pool of data that are different in a specific way and thus often should be considered separately when creating linear models
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Extrapolation
Using a linear model to predict values beyond those found within the domain of the data… can be highly unreliable, as it assumes that all other conditions still hold
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Influential Point
A point that results in a very different slope for a regression model if it is removed
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Outlier
A y-value that is far from its predicted value, resulting in a large initial residual… may or may not be an influential point
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Leverage
A data value whose x-value is far from the mean of x has high leverage, like an outlier in the x direction rather than y… may or may not be an influential point
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Lurking Variable
A hidden variable that simultaneously affects both variables in an association, accounting for the correlation that may appear between the two
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Residuals Plot
A scatterplot of the residuals versus the x-values of an association, with the x-axis denoting a residual of 0… a residuals plot with no apparent pattern (blob), bouncing above and below the x-axis, means that the determined LSR model is appropriate
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Re-Expression
Transforming a data set by taking the logarithm, square root, reciprocal, or some other math operation of ALL values in the data set to make it more conducive for linear regression
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Nearly Normal Residuals Condition
To perform inference for regression, the residuals must be \~Normally distributed \[linear normal probability plot\]
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Straight Enough Condition
To perform inference for regression, the association (scatterplot) studied must be \~linear \[check residual plot\]
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Equal Variance Condition
To perform inference for regression, the variability of y must be \~constant for all values of x; check the spread of the residuals around the predicted value of the residuals plot
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Standard Error of the Slope
The variation of the slope due to sampling variability, which is influenced by three factors: spread about the line (se), spread of the x-values (sx), and sample size (n)