1. Write the equation of the line of best fit using the slope-intercept formula $y = mx + b$. Show all your work, including the points used to determine the slope and how the equation was determined.
Here it seems like you would use your two points - (62,63) and (70,72) to find the equation of the best fit line. Use the slope formula and once finding the slope plug that and one point into the y=mx+b formula to find b.
2. What does the slope of the line represent within the context of your graph? What does the y-intercept represent?
The slope of the line would represent the average change in armspan with respect to height. The y intercept represents the predicted armspan if a person was 0 inches tall.
3. Test the residuals of two other points to determine how well the line of best fit models the data.
To do this you would take two other points on the graph and find the difference between the predicted y and the actual y. For example, if another point was (66,65), you would plug 66 into your best fit equation solve and then subtract the actual value (65) from your best fit value. A high residual indicates that the best fit line does not do a good job of modeling the data.
4. Use the line of best fit to help you to describe the data correlation.
If the line of best fit is positive, you may say that the data has a positive correlation. If the line of best fit has a slope of around one, you may say that a change in height yields an approximately equal change in armspan.
5.Using the line of best fit that you found in Part Three, Question 2, approximate how tall is a person whose arm span is 66 inches?
Use your line of best fit - plug in 66 as y
6. According to your line of best fit, what is the arm span of a 74-inch-tall person?
Use your line of best fit - plug in 74 as y
