Getting ready for your BCBA exam? You’re in the right place.

I created RBTExamPrep.com to give you the most realistic BCBA mock exam experience possible 185 questions designed to feel just like the real thing.

My goal isn’t just to help you pass, but to help you understand every concept deeply.
Whether you get a question right or wrong, you’ll see detailed feedback explaining why, so you’ll be ready for that type next time. I want you to walk into test day feeling confident, calm, and prepared.

Many students have shared that these questions felt almost identical to the real exam and that’s exactly what I was aiming for. I’d love to hear how you did please share your score in the comments below! It really helps encourage others who are preparing for the exam. 🙂

I built this site to keep high-quality BCBA prep resources free and accessible for everyone, which is why it’s supported by ads. If it helped you, it’d mean a lot if you shared it with your peers.

If you want to keep practicing, check out the BCBA section for more tests and study materials!

 

Results

#1. In the context of experimental design and inferential statistics, a Type I error is defined as a ‘false positive.’ This occurs when a researcher incorrectly rejects a true null hypothesis. Conversely, what is the term used to describe a ‘false negative,’ which occurs when a researcher fails to reject a false null hypothesis?

Type 0 error

Type II error

Validity error

Reliability error

A Type I error alpha error is a false positive meaning the experiment concludes there is an effect when in reality there isnt one A Type II error beta error is a false negative meaning the experiment concludes there is no effect when in reality there is one These concepts are fundamental in understanding the potential pitfalls and limitations of statistical hypothesis testing in experimental design directly impacting the validity of research findings Validity and reliability errors are broader concepts related to the quality of measurement and experimental control but not specific to false positives or false negatives in hypothesis testing

Next