Step 1 :The question is asking for the number of tests that will incorrectly find significance. This is also known as a Type I error, which occurs when we reject the null hypothesis when it is actually true.
Step 2 :The probability of a Type I error is equal to the significance level, which in this case is 5% or 0.05.
Step 3 :Therefore, if we conduct 900 tests, we would expect approximately 5% of them to incorrectly find significance.
Step 4 :Let's calculate this: \(tests = 900\), \(significance\_level = 0.05\), \(incorrect\_tests = tests * significance\_level = 45.0\)
Step 5 :Final Answer: Approximately \(\boxed{45}\) tests will incorrectly find significance.