Inference for negativist theory using numerically computed rejection regions
A negativist theory is a theory that asserts that an affect is absent. Negativist theories are common in statistics and require a test procedure to avoid biasing the conclusions in favor of accepting the theory. New critical value tables are provided and computational methods are introduced to ease practical difficulties with the resulting non-contiguous interval null. Simulations compare the power function of negativist testing to traditional hypothesis testing. A case study, using Canadian stock market data, does not always support efficient markets (an example of a negativist theory) and reverses previous studies using positivist hypothesis tests.
hypothesis testing interval hypothesis numerical solution