Terms:

bivariate data: data that consists of two variables. 

 

scatter plot:  a chart that uses x,y-coordinates to display values for two variables

 

association (positive, negative): a relation of dependency between two variables

 

positive association:  as x increases, y increases

 

negative association:  as x increases, y decreases

 

correlation:  the direction of association between two quantitative variables denoted by the value r that signifies the strength of the correlation between -1 and 1 

 

causation:  the relation of cause and effect

 

linear regression:  the relation between variables when the regression equation is linear.

 

regression equations:  (y-hat) y = a + bx where a is the y - intercept and b is the slope

 

least squares model:  the line that has the smallest value for the residual sum of squares in using the regression equation to predict y.

 

residual:  the prediction error; the difference between the actual value and the predicted value

( y - y-hat) 

 

slope:  rise over run 

 

y-intercept:  the point where a graph intercepts the y-axis

 

 

 

 

 MiniQuiz.doc

 Correlation & Regression Worksheet