Skip to ContentGo to accessibility pageKeyboard shortcuts menu
OpenStax Logo
Precalculus

Key Terms

PrecalculusKey Terms

Key Terms

correlation coefficient
a value, r,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)=mx+b,thenm<0. f(x)=mx+b,thenm<0.
extrapolation
predicting a value outside the domain and range of the data
horizontal line
a line defined by f(x)=b,f(x)=b, where bb is a real number. The slope of a horizontal line is 0.
increasing linear function
a function with a positive slope: If f(x)=mx+b,thenm>0.f(x)=mx+b,thenm>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−y1=m(x−x1)y−y1=m(x−x1)
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)=mx+bf(x)=mx+b
vertical line
a line defined by x=a,x=a, where aa 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
PreviousNext
Order a print copy
Citation/Attribution

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Attribution information
  • If you are redistributing all or part of this book in a print format, then you must include on every physical page the following attribution:
    Access for free at https://openstax.org/books/precalculus/pages/1-introduction-to-functions
  • If you are redistributing all or part of this book in a digital format, then you must include on every digital page view the following attribution:
    Access for free at https://openstax.org/books/precalculus/pages/1-introduction-to-functions
Citation information

© Dec 8, 2021 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.