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AP Statistics
Describing Relationships [The Practice of Statistics- Chapter 3]
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26 Terms
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regression line
A(n) ________ relating y to x has an equation of the form.
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Correlation
________ makes no distinction between explanatory and response variables.
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Extrapolation
________ is the use of a regression line for prediction outside the interval of values of the explanatory variable x used to obtain the line.
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statistical calculation
An observation is influential for a(n) ________ if removing it would change the results.
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doesnt guarantee
A value of r close to 1 or −1 ________ a linear relationship between two variables.
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slope
B is the ________, the amount by which y is predicted to change when x increases by one unit.
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standard deviation
Standardizing a variable converts its mean to 0 and its ________ to 1.
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quantitative variables
A scatterplot shows the relationship between two ________ measured on the same individuals.
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overall pattern
An outlier is an observation that lies outside the ________.
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least squares
The ________ regression line of y on x is the line that makes the sum of the squared residuals as small as possible.
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Residual plots
________ help us assess whether a linear model is appropriate.
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correlation itself
The ________ has no unit of measure.
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Correlation
________ only measures the strength of a linear relationship between two variables, never curved relationships.
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regression line
A(n) ________ is a model for the data, much like density curves.
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least squares
The mean of the ________ residual is always 0.
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Correlation
________ requires that both variables be quantitative.
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regression line
A(n) ________ summarizes the relationship between two variables, but only when one of the variables helps explain or predict the other.
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Correlation
________ and regression lines describe only linear relationships.
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regression line
A(n) ________ is a line that describes how a response variable y changes as an explanatory variable x changes.
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Correlation
________ indicates the direction of a linear relationship by its sign: r> 0 for a positive association and r
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To describe a scatterplot, follow the basic strategies of data analysis
look for patterns and important departures from those patterns
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IMPORTANT
Not all relationships have a clear direction that we can describe as a positive or negative association
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Correlation indicates the direction of a linear relationship by its sign
r > 0 for a positive association and r < 0 for a negative association
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Like mean and standard deviation, the correlation isnt resistant
r is affected by outliers
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residual = observed y
predicted y
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= y
y-hat