1.9.1: Key Terms

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Key Terms

correlation coefficient: a value, $r,$ between –1 and 1 that indicates the degree of linear correlation of variables, or how closely a regression line fits a data set.

decreasing linear function: a function with a negative slope: If $f (x) = m x + b, then m < 0.$

extrapolation: predicting a value outside the domain and range of the data

horizontal line: a line defined by $f (x) = b,$ where $b$ is a real number. The slope of a horizontal line is 0.

increasing linear function: a function with a positive slope: If $f (x) = m x + b, then m > 0.$

interpolation: predicting a value inside the domain and range of the data

least squares regression: a statistical technique for fitting a line to data in a way that minimizes the differences between the line and data values

linear function: a function with a constant rate of change that is a polynomial of degree 1, and whose graph is a straight line

model breakdown: when a model no longer applies after a certain point

parallel lines: two or more lines with the same slope

perpendicular lines: two lines that intersect at right angles and have slopes that are negative reciprocals of each other

point-slope form: the equation for a line that represents a linear function of the form $y - y_{1} = m (x - x_{1})$

slope: the ratio of the change in output values to the change in input values; a measure of the steepness of a line

slope-intercept form: the equation for a line that represents a linear function in the form $f (x) = m x + b$

vertical line: a line defined by $x = a,$ where $a$ is a real number. The slope of a vertical line is undefined.

x-intercept: the point on the graph of a linear function when the output value is 0; the point at which the graph crosses the horizontal axis

y-intercept: the value of a function when the input value is zero; also known as initial value

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