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Software systems and computational methods
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Algorithmization of the process of analyzing the reliability of online questionnaire data
Martyshenko Natal'ya Stepanovna

PhD in Economics

Professor, the department of International Marketing and Trade, Vladivostok State University of Economics and Service

690014, Russia, Primorsky Krai, Vladivostok, Gogolya Street 41

natalya.martyshenko@mail.ru
Другие публикации этого автора
 

 
Martyshenko Sergei Nikolaevich

PhD in Technical Science

Professor, Department of Mathematics and Modeling, Vladivostok State University of Economics and Service

690014, Russia, Primorskii krai, g. Vladivostok, pr. Krasnogo Znameni, 96, kv. 17

sergey.martishenko@vvsu.ru

Abstract.

With the proliferation of online forms design services for online surveys, the number of researchers using questionnaires in research practice has increased significantly. One of the problems that was present in the traditional form of the survey on paper and was transferred to online surveys is the problem of data reliability. Most researchers using online surveys have higher queries to automate research. They are not ready to make significant efforts to increase the reliability of the data. In this paper, we propose to consider an algorithm for automating the process of analyzing the reliability of questionnaire data. The proposed algorithm is based on the use of a sliding exam procedure for testing individual multidimensional observations obtained during an online survey. The main hypothesis underlying the developed method consists in the fact that the subordination of the questionnaire questions to some general topic leads to some latent connections between answers that are violated by random answers. A multi-dimensional statistical criterion was developed for testing personal data. The method is very simple to use and is available even for not sophisticated researchers.

Keywords: Internet service, nominal features, computer technology, sliding exam, criterion fquality of data, latent connections, multivariate statistical methods, online survey, data quality, questionnaire

DOI:

10.7256/2454-0714.2018.4.28367

Article was received:

18-12-2018


Review date:

13-12-2018


Publish date:

10-01-2019


This article written in Russian. You can find full text of article in Russian here .

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