Correlation requires clearly identified explanatory and response variables.
Regression requires clearly identified explanatory and response variables.
Scatterplots require that both variables be quantitative.
Every LSRL will pass through the coordinate point (mean of x, mean of y).
Correlation changes as units of the variables change.
The LSRL minimizes the distances between the actual response variable values and the predicted values.
Switching the explanatory and response variables will NOT change the least-squares regression line.
The slope of the line is very senstive to outliers with large residuals.
The value of the coefficient of determination that is close to 1 does NOT guarantee that the relationship between the variables is linear.
The value of the coefficient determination close to 1 show that the explanatory variable is the cause of the response variable.
The x variable is known as the response variable.
The strongest correlation is equal to only 1.