Chapter 10 - Correlation and Regression

straight line

A(n) ________ satisfies the** least- squares property** if the sum of the squares of the residuals is the smallest sum possible.

Common errors

________ involving correlation: assuming that correlation implies causality, using data based on averages, ignoring the possibility of a nonlinear relationship.

R

________ is very sensitive to outliers in the sense that a single outlier could dramatically affect its value.

confidence interval

A** ________** is a range of values used to estimate a population parameter.

coefficient of determination

The** ________** is the proportion of the variation in y that is explained by the regression line.

residual plot

A** ________** is a scatterplot of the (x, y) values after each of the y- coordinate values has been replaced by the residual value y- y hat.

total deviation

The** ________** of (x, y) is the vertical distance y- y bar, which is the distance between the point (x, y) and the horizontal line passing through the sample mean y hat.

regression equation

The ________ algebraically describes the regression line.

prediction interval

A** ________** is a range of values used to estimate a variable.

R

________ measures the strength of a linear relationship.

correlation

A  ____________ exists between 2 variables when the values of 1 variable are somehow associated with the values of the other variable

 linear correlation

A ______________ exists between two variables when there is a correlation and the plotted points of paired data result in a pattern that can be approximated by a straight line

linear correlation coefficient

The __________________ r measures the strength of the linear correlation between the paired quantitative x values and y values in a sample