Stop wasting time on significance tests #MRX

Have you ever conducted a research project and NOT done any significance tests?

Have you ever run a series of significance tests and wondered why you bothered to do them?

pie chart significance testLet’s think about why we do research projects and why we do significance testing. First of all, research isn’t worth doing unless the methodology is designed very carefully with appropriate sample sizes, great questions, and high standards of data quality. It should be designed with very clear research objectives in mind, with potential outcomes carefully thought out, with potential action steps carefully thought out. Quality research studies are conducted with measures of success clearly outlined before the research is carried out.

If all of these things are in place, then I challenge you to consider why you even bother with significance testing. A research study with clearly thought out objectives should be accompanied by specific hypotheses that lead to specific outcomes. Your well planned out study determined that Product A must generate scores that are at least X% better than Product B before Product A is identified as a success. If it does, then it makes sense to proceed with launching Product A.

So if you already know that you are seeking improvements of size X%, there is zero reason to conduct significance tests. Your measure of success has been predetermined. You already know that, based on your high quality research design, the difference is large enough to warrant moving forward with the launch.

In other words, if you need to run a signficance test to determine if a difference is important, then the difference is for sure not important at all. Significance tests aren’t required.

7 responses

  1. I certainly agree that many don’t properly plan their research, and even more do not make decisions based on research. Yet the research plan you suggest essentially integrates significance testing into the decision. You can’t make a meaningful statement about what size of change matters without some understanding of natural variability in the data, right? It sounds like you are describing something a lot like the critical values that we used to use in the old days, stated in terms of the data values rather than a value of a z, t or other statistic.

    1. You’re absolutely right. The message is do all the correct planning ahead of time and your research will be better off. In my line of work, where sample sizes are regularly in the hundreds of thousands, significance tests are completely useless. Every single test, no matter how tiny the effect size, is significant. Brain work is the most important test.

  2. While I agree that it is really important not to let significant tests do the thinking for us, significance tests still have an important place in the research process, as Chuck mentioned.

    The main problem is probably that the further we get from the classroom, the more our habits and years of experience begin to work against us. -that AND the fact that so many of us who are fresh from the classroom didn’t understand statistics to the degree that experienced researchers do. So the old folks are messing it up with their bad habits. The young folks are messing it up with their lack of comprehensive understanding. And the people in the middle are just plain messing it up.

    1. 🙂 Everyone’s messing it up. I think I agree with you on all your points.

  3. A really good reminder – thanks. Sig tests seem to be in every report these days!

  4. Unless I am missing something, this seems a bit “silly.” Of course, significance does not equal importance — especially if you have a pre-set level as a goal/measure. Significant testing is meant to ID those differences that cannot be attributed to chance as defined by one’s choice of confidence intervals, etc.

    1. I think a lot of people don’t even bother thinking about their research objectives or their 300 pages of crosstabs. They just look for whatever is statistically significant (or not) and run with it regardless of whether it makes sense. They let the significance tests do their thinking for them which, of course, they can not.

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