Model a real-world scenario with a linear equation, then use the model to predict forward, solve backward, and verify with a table.
Modeling means running the whole cycle: spot the starting amount and the steady rate in a real situation, write y = mx + b, and then actually USE it -- predict a value forward, solve for an unknown backward, and double-check with a small table.
This project is not new material -- it chains together everything from the last seven weeks onto one real scenario. Building a 3-row check table at the end is the fastest way to catch a setup mistake before it spreads through the whole project.
Mastery looks like: Given a multi-part real scenario, they build y = mx + b, use it to predict forward and solve backward, and verify with a table.
Common stumbles: Building the model correctly but then plugging numbers into the wrong side (solving for x when they should compute y); skipping the check table and missing an arithmetic slip.