And anyway, if all of this hypothesis testing was easy enough so anybody could understand it, how do you think statisticians would stay employed?
ERC is looking for high-risk, high-gain, investigator and hypothesis-driven projects.
It is important to keep in mind that a successfully constructed hypothesis is essential to an overall successful ERC application.
Additional posts in our Knowledge Base can offer important guidelines to follow.
When your study analysis is completed, the idea is that you will have to choose between the two hypotheses.
If your prediction was correct, then you would (usually) reject the null hypothesis and accept the alternative.This seemingly obvious aspect of research can be deceptively difficult to pin down, as researchers often have an unstated sense of what they want to achieve in a study (and excitement about doing so) that makes it challenging to clearly state a research question.Glenn Firebaugh (2008) identified two key criteria for research questions: questions must be researchable and they must be interesting.Then the only other possible outcome would be that variable A and variable B are to represent the null case. In some studies, your prediction might very well be that there will be no difference or change.In this case, you are essentially trying to find support for the null hypothesis and you are opposed to the alternative.Unlike many features of ERC, hypothesis is expected by many reviewers in many disciplines, although you will not find the word ERC strives for frontier research that reflects a new ground breaking understanding of basic research.By definition, research at and beyond the frontiers of understanding is an intrinsically risky venture, proposing to progress new and exciting research areas.We can see that the term "one-tailed" refers to the tail of the distribution on the outcome variable. For instance, let's assume you are studying a new drug treatment for depression.The drug has gone through some initial animal trials, but has not yet been tested on humans.If your original prediction was not supported in the data, then you will accept the null hypothesis and reject the alternative.The logic of hypothesis testing is based on these two basic principles: , and sometimes we just have to do things because they're traditions.