Coefficient of determination
The fraction of the variation in the values of y that is accounted for by the least-squares regression line of y on x.
Correlation
Measures the direction and strength of the linear relationship between two quantitative variables.
Explanatory variable
A variable that may help explain or influences changes in a response variable.
Extrapolation
The use of a regression line for prediction far outside the interval of values of the explanatory variable x used to obtain the line.
Influential
An observation that if removed it would markedly change the result of the calculation.
Least-squares regression line
Line that makes the sum of the squared vertical distances of the data points from the line as small as possible.
Negative association
Above-average values of one variable tend to accompany below-average values of the other, and vice versa.
Outlier
An observation that lies outside the overall pattern of the other observations.
Overall pattern
Can be described by the direction, form, and strength of the relationship.
Positive association
Above-average values of one variable tend to accompany above-average values of the other, and below-average values also tend to occur together.
Predicted value
read as "y hat
Regression line
A line that describes how a response variable y changes as an explanatory variable x changes.
Residual
The difference between an observed value of the response variable and the value predicted by the regression line.
Residual plot
Helps us assess how well a regression line fits the data.
Response variable
A variable that measures an outcome of a study.
Scatterplot
Plot that shows the relationship between two quantitative variables measured on the same individuals.
Slope
The amount by which y is predicted to change when x increases by one unit.
Standard deviation of the residuals (s)
This value gives the approximate size of a "typical" or "average" prediction error (residual).
y intercept
The predicted value of y when x = 0.
Coefficient of determination
The fraction of the variation in the values of y that is accounted for by the least-squares regression line of y on x.
Correlation
Measures the direction and strength of the linear relationship between two quantitative variables.
Explanatory variable
A variable that may help explain or influences changes in a response variable.
Extrapolation
The use of a regression line for prediction far outside the interval of values of the explanatory variable x used to obtain the line.
Influential
An observation that if removed it would markedly change the result of the calculation.
Least-squares regression line
Line that makes the sum of the squared vertical distances of the data points from the line as small as possible.
Negative association
Above-average values of one variable tend to accompany below-average values of the other, and vice versa.
Outlier
An observation that lies outside the overall pattern of the other observations.
Overall pattern
Can be described by the direction, form, and strength of the relationship.
Positive association
Above-average values of one variable tend to accompany above-average values of the other, and below-average values also tend to occur together.
Predicted value
read as "y hat
Regression line
A line that describes how a response variable y changes as an explanatory variable x changes.
Residual
The difference between an observed value of the response variable and the value predicted by the regression line.
Residual plot
Helps us assess how well a regression line fits the data.
Response variable
A variable that measures an outcome of a study.
Scatterplot
Plot that shows the relationship between two quantitative variables measured on the same individuals.
Slope
The amount by which y is predicted to change when x increases by one unit.
Standard deviation of the residuals (s)
This value gives the approximate size of a "typical" or "average" prediction error (residual).
y intercept
The predicted value of y when x = 0.