{"id":603,"date":"2018-05-14T08:30:00","date_gmt":"2018-05-14T12:30:00","guid":{"rendered":"http:\/\/darwin.eeb.uconn.edu\/uncommon-ground\/?p=603"},"modified":"2018-05-13T20:05:45","modified_gmt":"2018-05-14T00:05:45","slug":"causal-inference-in-ecology-the-challenge-of-falsification","status":"publish","type":"post","link":"https:\/\/darwin.eeb.uconn.edu\/uncommon-ground\/blog\/2018\/05\/14\/causal-inference-in-ecology-the-challenge-of-falsification\/","title":{"rendered":"Causal inference in ecology – The challenge of falsification"},"content":{"rendered":"

Causal inference in ecology – links to the series<\/a><\/p>\n

It sounds so simple. You have a hypothesis. You design an experiment to test it. If the predicted result doesn\u2019t happen, reject the hypothesis and start over. That\u2019s how science works, right? We can\u2019t prove<\/strong><\/em> a hypothesis, but we can reject them. That\u2019s how we make progress. That\u2019s what makes science empirical. End of story right? Would I be asking that question if it were?<\/p>\n

Let\u2019s look at the logic a bit more carefully.<\/p>\n

The hypothesis we\u2019ve been using as an example is simple: If we apply nitrogen fertilizer, the yield of corn will increase. Our experiment is to till the soil in a field thoroughly, plant genetically uniform1<\/a><\/sup> corn, and apply fertilizer on one part of the field and not the other. The test of our hypothesis is whether yield in the fertilized part of the field exceeds yield in the unfertilized part of the field. For the sake of argument, let\u2019s suppose that the fertilized part of the field has the same yield (or less) than the unfertilized part of the field. Would you conclude that adding nitrogen fertilizer doesn\u2019t increase corn yield? I wouldn\u2019t, and I\u2019ll bet you wouldn\u2019t either. Why wouldn\u2019t we conclude that? My logic would run like this:<\/p>\n