In the realm of scientific research, headlines often proclaim findings such as 'New drug shows no effect' or 'Study finds no evidence a policy works.' While these statements may appear definitive, they mask a deeper controversy within the scientific community.
The disagreement centers on the interpretation of what it means to say there is 'no effect.' Neyman and Fisher, two prominent statisticians, have fundamentally different approaches to causal inference, leading to varied conclusions in research.
Understanding these differing perspectives is essential for accurately interpreting research findings and their implications for policy and practice. The debate continues to shape how scientists approach causal inference today.