Statistical Thinking

In statistical thinking there is a tenancy towards conservatism. The investigators, enthusiastic to obtain positive results, may prefer favorable conclusions and may tend to over-interpret the data. It is the statistician's role to add objectivity to the interpretation of the data and to advocate caution.

On the other hand, the investigators may say that conservatism and science are incompatible. If one is too cautious, if one is always protecting oneself against the worst-case scenario, then one will not be able to make bold new discoveries.

Which of the two approach do you prefer?

When you formulate your answer to this question it may be useful to recall cases in your past in which you where required to analyze data or you were exposed to other people's analysis. Could the analysis benefit or be harmed by either of the approaches?

For example, many scientific journal will tend to reject a research paper unless the main discoveries are statistically significant (p-value < 5%). Should one not publish also results that show a significance level of 10%?

Which of the two approach do you prefer?

We as humans tend to always be biased in one way or the other. Even if we are consciously trying to avoid it, our subconscious can get in the way. So, whether you are being objective or subjective, it applies to a lot of different fields even outside statistics like the culinary arts, journalism, politics, and even education. When it comes to the two approaches, I do think objectivity wins. However, it depends on the topic. One cannot make objective decisions or come up with objective solutions to blanket issues or problems. In order to be truly objective, you must look at things on a smaller and more specific scale to get a good idea of all the factors.

The same goes for publishing results under a 5% significance level or 10% significance level. I believe it depends on the topic or study being done and the effect of the significance level on that study. For example, if there is a 10% significance level that a certain cosmetic can actually cause cancer, then maybe that study should be published to increase awareness. However, if there is a 10% significance level that people tend to prefer lighter eyes to darker eyes then it would be better to avoid printing it simply because of the subjective nature of the study. The study regarding cancer would have scientific research done on it outside of surveys and questionnaires.

It’s important to recognize the environment and the circumstances surrounding the questions or study or calculation in order to determine how inherently careful one must be while doing it. Especially when it comes to small samples, even a careful observation could lead to people thinking you are being subjective maybe because of the sample taken. It is a question that cannot be answered objectively but must be taken into account in each study.


Yakir, B. (2011). Introduction to Statistical Thinking (With R, Without Calculus). Jerusalem, IL: The Hebrew University of Jerusalem, Department of Statistics.

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