23 terms

# AP Statistics Chapter 3 VOCAB

#### Terms in this set (...)

Response Variable
measures an outcome of a study
Explanatory Variable
may help explain or predict changes in a response variable
Scatterplot
shows the relationship between two quantitative variables measured on the same individuals
Positive Association
data points that generally go upward from left to right, somewhat linear
Negative Association
data points that generally go downward from left to right, somewhat linear
Strength
determined by how closely the points follow a clear form
Outlier
an individual value that falls outside the overall pattern of the relationship
Correlation
measures the direction and strength of the linear relationship between two quantitative variables
Regression Line
a line that describes how a response variable y changes as an explanatory variable x changes
Extrapolation
the use of a regression line for prediction outside the range of values of the explanatory variable x used to obtain the line
Least-Squares Regression Line (LSRL)
the line that makes the sum of the squared vertical distances of the data points from the line as small as possible (best-fit line on a scatter plot)
Residual
the difference between an observed value of the response variable and the value predicted by the regression line (a.k.a. prediction error)
Residual Plot
a scatterplot of the regression residuals plotted against the explanatory variable
Coefficient of Determination
the portion (%) of the variation in the response variable (y) that is explained by the least-squares regression line of y and x
Lurking (Confounding) Variable
a variable that is not among the explanatory or response variables in a study and yet may influence the interpretation of relationships among those variables
Residual (formula)
Least squares regression line (formula)
coefficient of determination (symbol)
correlation coefficient (symbol)
predicted value (symbol)
D.O.F.S.
direction, outliers, form, strength - all things that should be addressed when describing the relationship between two quantitative variables
standard deviation of the residuals
the approximate size of a typical prediction error (residual) when we use the least squares regression line to predict the value of a specific response variable
standard deviation of the residuals (symbol)
s