describing real world data with variables and equations

a clear association between the independent variable (x) and the dependent variable (y)

measures the direction and strength of the linear relationship between two quantitative variables; symbolized by r

process of constructing a curve, or mathematical function, that has the best fit to a series of data points, possibly subject to constraints

the independent variable; usually the x

the process of drawing conclusions from data subject to random variation, for example, observational errors or sampling variation

models the relationship between a  dependent or response variable y and one or more explanatory  or independent variable(x) by finding the least square regression line

a linear model used to fit a line to a data set using only summary points; more accurate to use if there are outliers

a relationship between two sets of data such that a decrease in one set of data corresponds to an increase in the other

a relationship between two sets of data such that an increase in one set of data corresponds to an increase in the other

modeling process by which the equation of a parabola is found that “best fits” a given set of data

the dependent variable; usually the y

the extent to which a linear model does or does not fit a set of data; found by determining the distance of the data points from the line that minimizes that distance.

data that involve two variables that may be related to each other

displays the direction, form, and strength of the relationship between two quantitative variables.

a line that is drawn to show the approximate relationship formed by the plotted points; the equation of a best fit line

a prediction made within known values

 a prediction made beyond the known values

a way to determine what type of polynomial function will best model bivariate data.