-Explanatory variable(x, horizontal axis) -Response variable (y, vertical axis) y= b0+b1x -Least Squares Regression Line: -Slope interpretation: For every one unit increase in x variable, the predicted change in the response variable will increase/decrease by slope with units. -R2: percentage of variability that can be explained by the relationship between x and y -Intercept interpretation: When the x variable is zero, the predicted response variable will be intercept with -Does the intercept make sense? abut whether or not it is possible to have that response when x is zero –think -Extrapolation: data being tested falls outside of the observed range. t = b1−0/ SEb1 -Test statistic: - 0 < r < 0.3—weak relationship; 0.3 < r < 0.7—moderate relationship; 0.7 < r < 1—strong relationship (absolute of r)
-Explanatory variable(x, horizontal axis) -Response variable (y, vertical axis) -Least Squares Regression Line: y= b0+b1x -Slope interpretation: For every one unit increase in x variable, the predicted change in the response variable will increase/decrease by slope with units. -R2: percentage of variability that can be explained by the relationship between x and y -Intercept interpretation: When the x variable is zero, the predicted response variable will be intercept with -Does the intercept make sense? –think abut whether or not it is possible to have that response when x is zero -Extrapolation: data being tested falls outside of the observed range. -Test statistic: t = b1−0/ SEb1 - 0 < r < 0.3—weak relationship; 0.3 < r < 0.7—moderate relationship; 0.7 < r < 1—strong relationship (absolute of r)