Linear Regression Word Scramble
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Question | Answer |
input variable | the independent variable |
line of best fit | a line whose equation represents the smallest possible differences between the squares of observed minus predicted values on a line |
linear correlation coefficient | the strength of a linear relationship between two variables, determined by the preciseness of shift in y as x increases. |
linear regression | the straight line that best describes the relationship between two variables |
negative correlation | a correlation in which an increase in x leads to a decrease in y. |
ordered pairs | a mathematical expression (x, y) where x is the input variable written first, and y is the output variable written second. |
output variable | the dependent variable |
positive correlation | a correlation in which an increase in x leads to an increase in y. |
predicted value | the value of y calculated by modeling a particular value of x with a prediction equation. |
prediction equation | an equation that models a mathematical relationship between x and y with an algebraic expression. |
scatter plot | a plot of all the ordered pairs of bivariate data on a coordinate axis system. |
slope | the ratio of the rise over the run of a line. |
bivariate data | data that describes two characteristics for each observation |
correlation coefficient | the numerical measure of the direction and strength of a linear association |
interpolation | using the line of regression to predict a y-value for an x-value within the x-data |
extrapolation | using the line of regression to predict a y-value for an x-value outside of the x-data set |
residual | the difference between the observed value of y and the predicted value of y |
residual plot | a scatterplot of the residuals plotted to the x-values or predicted y-values |
coefficient of determination | r squared measures the percentage of total variation in the response variable that is explained by the least-squares regression line |
Created by:
rbankston
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