Ch 9.2: Linear Regression
regression line (
line of best fit
the line for which the sum of the squares of the residuals is a minimum
the difference between the
y-value and the
y-value (can be positive, negative, or 0)
equation of a regression line
y(hat) = mx + b
y-value for a data point
predicted y-value (on a regression line)
the regression line
always passes through point
Given a set of data and a corresponding regression line, describe all values of x that provide meaningful predictions for y
Prediction values are meaningful only for x-values in (or close to) the range of the original data.
In order to predict y-values using the equation of a regression line, what must be true about the correlation coefficient of the variables?
The correlation between variables must be significant.
Is it appropriate to use a regression line to predict y-values for x-values that are not in (or close to) the range of x-values found in the data?
It is not appropriate because the regression line models the trend of the given data, and it is not known if the trend continues beyond the range of those data.
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