14.9: Key Terms
- Page ID
- 94726
\( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)
- best-fit linear regression model
- an equation of the form that provides the best-fit straight line to the (x, y) data points
- beta
- the measure of the volatility of a stock as compared to a benchmark such as the S&P 500 index
- correlation
- the measure of association between two numeric variables
- correlation coefficient
- a measure of the strength and direction of the linear relationship between two variables
- linear correlation
- a measure of the association between two variables that exhibit an approximate straight-line fit when plotted on a scatter plot
- method of least squares
- a mathematical method to generate a linear equation that is the “best fit” to the points on the scatter plot in the sense that the line minimizes the differences between the predicted values and observed values for y
- prediction
- a forecast for the dependent variable based on a specific value of the independent variable generated using the linear model
- residual
- the difference between an observed y-value and the predicted y-value obtained from the linear regression equation
- scatter plot (scatter diagram)
- graphical display that shows values of the independent variable plotted on the x-axis and values of the dependent variable plotted on the y-axis