Correlation measures the strength and direction (type) of linear relationships and is quantified by using the correlation coefficient (r-value).

r = _________________

Using the information from the output you can write the equation for the regression in the y = a + bx form. Statdisk calls the values by a different name, but they follow the same pattern. See the "Regression Results" on the output for the info and translate them into our notation before writing the equation for the "least squares line."

a = _________ b= _________

The square of the correlation, r2, is the proportion of the variation in the values of y that is explained by the linear relationship with x.

r2 = ________

3. Correlation and regression

Find the correlation coefficient for this relationship.

What proportion of variation can be explained by the linear relationship between the

two variables?

Write the linear equation for the least squares line for this relationship?

Use the equation to predict the age of a child with a vocabulary size of 2,200.

Use the equation to predict the vocabulary size the corresponds to an eight-year-old

child.

Why or why not should you use this model predict the vocabulary size of an eight-year-

old child?

Final analysis: Do you think that there is a relationship between age and vocabulary size?

4. Revisit/re-evaluate the question from the beginning. Do you have any new evidence suggesting this to be true or false? Explain.