How to guarantee the results of investigations with limited statistical information

2019

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1088/1757-899x/657/1/012075
Data confidence 70 medium
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It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Abstract What kind of problems do researchers usually have after investigations connected with different physical processes (e.g., temperature, deterioration, pressure, vibration, and so forth)? In many mathematical papers, textbooks and reference books it is suggested that 340-360 statistical data are needed to obtain the right conclusion by experimentation [1-3]. In these cases, much money (and time, days and even months) will be required. Usually, researchers try to restrict the amount of statistical data to 3, 5, 10 or 30 data points. But in this case, they do not have enough information to determine the trustworthiness of their deductions. Our task is the following: to solve this problem and demonstrate the fact that if there are even only three points of observation, we can still obtain a convincing response/result. It is rather difficult to overestimate the significance of this achievement in practice.