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