Summary: Every decision a BCBA makes runs on two assumptions: that your data are accurate, and that you ran the program the way it was written. Reliability (checked with IOA) is about the data. Treatment fidelity (also called procedural or treatment integrity) is about the procedure. When either one slips, the team can't tell whether an intervention worked, and that's how a client ends up on the wrong plan. Your job is to protect both, every session.
Let me tell you the thing that took me a while to really feel as an RBT. The graph the BCBA stares at when they decide to keep, change, or drop a program is only as honest as two things you control: whether your numbers reflect what the client actually did, and whether you ran the plan the way it was written. Mess up either one and the graph lies. Not on purpose. It just stops describing reality.
This is a new task on the 3rd-edition outline, and I think it's there because the BACB wants RBTs who understand the stakes, not just the formulas. You can calculate IOA in your sleep and still not get why it matters. So we're going to spend most of our time on the "why this hurts the client" part, and link the arithmetic to where it lives elsewhere in this section.
Two different questions
People blur these constantly, so pin them apart now and you'll thank yourself on exam day.
Data reliability asks: do two people, watching the same behavior at the same time, write down the same thing? If yes, your data probably reflect the client. If no, your data reflect the observer, and that's worthless. We check this with interobserver agreement (IOA).
That's the free preview of Data Reliability and Treatment Fidelity. The complete guide, plus all 851 practice questions and 3 full exams, is in the study pack and the book.