Do you notice a pattern between a student’s weight and the weight of their backpack? It is hard to tell from this table of data, but a graphical display might help. Create a scatterplot to investigate the possibility.

The amount of weight that a student can comfortably carry depends on his or her body weight. Put the explanatory variable - student weight - on the horizontal axis. The response variable - backpack weight - goes on the vertical axis.

Look at the data and choose appropriate starting points and increments for your graph.

A starting point of 100 pounds on the horizontal axis works nicely, and a tick mark every 10 pounds is appropriate. On the vertical axis, you could begin at 20 pounds and make marks at 2-pound increments.

Now begin plotting the data points. Crystal weighs 120 pounds. Her backpack weighs 26 pounds.

Now add the points corresponding to the six remaining club members to complete the graph.

The scatterplot reveals a pattern in the two variables being measured.

The graph seems to indicate that lighter students tend to carry lighter backpacks, while heavier students carry heavier packs. When larger numbers tend to be paired with larger numbers, we say the variables have a positive association.

The pattern of points appears to be close to a straight line, which indicates a linear relation. The points are tightly clustered close to the line, which indicates what we think of as a strong relation. (You will soon convert this intuition into an actual number!)