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The Euclid Statistical Matrix Tool 

 
Curtis Tilves1, Saeed 
Yekaninejad2, Tetsuro Hayashi3, 
Eman Eltahlawy4, Eugene 
Shubnikov5, Shalkar Adambekov1 
 
1University of Pittsburgh Graduate School of Public 

Health, USA;  
2Department of Epidemiology and Biostatistics, 

School of Public Health, Tehran University of 

Medical Sciences, Iran;  
3Jikei University School of Medicine, Tokyo, Japan; 
4Environmental Health and Occupational Medicine 

Department, National Research Center, Egypt; 
5Institute of Internal Medicine, Novosibirsk, Russia  

Vol. 6, No. 1 (2017)   |   ISSN 2166-7403 (online) 
DOI 10.5195/cajgh.2017.283 |   http://cajgh.pitt.edu 

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TILVES 
 

 
This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by theUniversity Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

The Euclid Statistical Matrix Tool 
 
Curtis Tilves1, Saeed Yekaninejad2, 
Tetsuro Hayashi3, Eman Eltahlawy4, 
Eugene Shubnikov5, Shalkar 
Adambekov1 
 
1University of Pittsburgh Graduate School of 
Public Health, USA;  
2Department of Epidemiology and 
Biostatistics, School of Public Health, Tehran 
University of Medical Sciences, Iran;  
3Jikei University School of Medicine, Tokyo, 
Japan;  
4Environmental Health and Occupational 
Medicine Department, National Research 
Center, Egypt;  
5Institute of Internal Medicine, Novosibirsk, 
Russia 

Editorial 

Global health has definitions of varying levels 

of complexity, but in essence, it can be summarized as a 

framework of methods aimed at improving population 

health. Through both observation and intervention, 

global health researchers can monitor diseases and 

employ interventions to prevent adverse health outcomes 

by reducing their incidence. Given the large variability in 

the human population, public health and medical research 

investigations require rigorous methods and analytics in 

order to evaluate and to determine the validity of 

conclusions. Moreover, these standardized research 

methods are critical for comparison of findings across 

geographic boundaries, ethnic groups, and time periods.  

However, a lack of skills in the areas of research methods 

and statistical evaluation is a common limitation among 

researchers globally, especially in developing countries 

where research productivity is lower compared to 

developed countries1-3. This debilitating condition, which 

is found worldwide and has a far-reaching impact on 

publications and tenure, is known as “Stataphobia”. 

Stataphobia is a phrase which describes the 

‘abnormal fear of research design and statistics’4. The 

fear of statistics, or not having access to a statistician for 

help, is a major problem for many scientists, as a lack of 

properly performed methods dooms submissions to 

rejection for articles, grants, and other scientific 

communications.  It can affect multiple layers of global 

health, as major policy decisions based on inaccurate, 

incomplete, or old statistics can waste resources without 

positively impacting the health issue. The rejection of 

publications based on poor statistical methods can have a 

profound impact on the number of scientific publications 

and the competitiveness of research coming out of many 

countries, especially those that are non-Western 

countries.  

Publication statistics from the country of 

Kazakhstan highlight the disparities present in global 

health research productivity. Adambekov et al. discusses 

how health research contributes to only 7% of the overall 

number of publications coming from Kazakhstan, a trend 

shared by other Central Asian countries5. Even when 

compared with other countries of a similar population 

size or GDP, the publication rates are indeed low6.  In 

fact, despite the low number of publications coming from 

this country, Kazakhstan is in the highest output of 

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CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 
 

 

This work is licensed under a Creative Commons Attribution 4.0 United States License. 
 

This journal is published by theUniversity Library System of the University of Pittsburgh as part  
of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 
Central Asian Journal of Global Health 

Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

medical publications in Central Asia, highlighting the 

need for regional improvement6-8 (see Figure 1). We 

suggest that Stataphobia plays an important role in this 

phenomenon, as without proper research methods and 

publication output, not only is scientific progress 

impeded in these countries, but health research—and 

public health policy as a whole—suffers.

 
Figure 1: General scientific publication trends of Central Asian countries for 1996-2015 

It is believed that the increase in publications from Kazakhstan starting in 2012 are likely from the addition of a 

policy that PhD candidates must submit at least one article to a journal with an impact factor greater than 09. 

 

The basic understanding of statistics usually 

comes in the higher education settings. Students in 

health, especially those who are medical and nursing 

students, require an understanding of statistics to perform 

clinical research. Without an understanding of research 

publications, it is most difficult to improve clinical 

performance. Even medical students not planning to 

perform research must be able to understand statistics in 

order to comprehend clinical research and to understand 

how it may apply to their patients. In other areas of 

national and international work, a lack of understanding 

of statistical concepts can cause even larger issues. For 

example, a lack of understanding of statistics would 

make it impossible to accurately interpret and evaluate 

global health trends and their applications to public 

health programs. This has had an impact on policies 

0

500

1000

1500

2000

2500

1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

General Scientific Publications from Central Asian Countries 

Kazakhstan Kyrgyzstan Tajikistan Turkmenistan Uzbekistan

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TILVES 

 
This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by theUniversity Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

regarding immigration, where statistics have recently 

been found to be lacking and inaccurate10. Improper 

statistical training can also result in developing countries 

becoming exporters of “raw” research data to developed 

countries because they are unable to properly analyze and 

publish that data. This has the effect of furthering the 

establishment of “scientific banana republics” in 

developing nations, where the economic benefit and the 

directions of health research are ultimately under the 

control and influence of already developed countries11.  

Thus, an intervention on a global scale is 

required to reduce the impact of Stataphobia on research, 

especially in developing countries. This can lead to 

improved health and can aid in establishing evidence-

based programs. One area to intervene on is in the initial 

teaching of statistical methods and in the access to those 

teachings. Often, students find statistics difficult and 

boring.  Stataphobia can take hold in the classroom, 

where some learners of statistics become frightened by 

the non-intuitive concepts they most need to learn in 

order to produce the best research possible. Students 

enter the classroom coming from a variety of 

backgrounds, from math majors to philosophy majors, 

thus having marked differences in existing knowledge 

and interest in statistics. Furthermore, students may just 

learn certain topics best from different approaches than 

the approach the professor is using, and these ‘best 

approaches’ may differ from student to student as well as 

from topic to topic. Is it possible to intervene on the 

classroom, influencing learning through multiple 

approaches on the same topic? Moreover, can this be 

done in countries facing language barriers to 

international publications and/or face limitations in 

teaching resources? Cue: The Euclid Statistical Matrix. 

Through the Research Methods Library at the 

Library of Alexandria (RMLA), Egypt, we have 

constructed a free, malleable, and multilingual tool 

designed to help learners of basic statistical methods12. 

The Euclid Statistical Matrix is a compilation of some of 

the most popular YouTube videos which teach statistics. 

In the Euclid Matrix, the columns of the matrix serve to 

house content for a particular YouTube channel, and the 

rows contain various statistical topics or lessons (Figure 

2). 

Matrix link: 

http://www.pitt.edu/~super1/ResearchMethods/Statistics

Matrix.htm 

Using this format, if one wanted to learn about 

variance, they may move down to the “Variance” row, 

and then choose from a Khan Academy video, a Brandon 

Foltz lecture, a Statslectures video, etc., providing 

multiple presentation approaches to a similar topic. 

This approach has many strengths. The most 

important strength is that the Statistical Matrix is easily 

accessible. The use of YouTube videos as a primary 

educational source provides a format that is freely 

accessible by all and allows for multiple visual 

representations of and approaches to a topic. Two, it 

allows the professor to integrate their own lectures into 

the matrix, making it an adaptable tool for the classroom. 

By allowing multiple presentation formats (video, 

PowerPoint, online books, etc.), a student can utilize 

several matrix resources to understand the difficult topic. 

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CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 
 

 

This work is licensed under a Creative Commons Attribution 4.0 United States License. 
 

This journal is published by theUniversity Library System of the University of Pittsburgh as part  
of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 
Central Asian Journal of Global Health 

Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

Three, it utilizes much of the high quality statistical open 

access content that currently exists on the Internet. Four, 

the Euclid Matrix has the ability to be a living matrix.  As 

more quality videos are found or created, the Matrix may 

be updated to better reflect the needs of statistics learners. 

Finally, the concept of the matrix is easy to implement in 

other languages. Statistics is already hard enough to 

learn, and if your native language is not English, then 

learning statistics will be even more difficult. By re-

creating the Euclid Statistics Matrix using educational 

materials developed in the other languages, we remove 

this language barrier issue while also utilizing the 

resources available in non-English languages and 

empowering the global researcher/lecturer communities. 

To this point, we have developed the Euclid Statistical 

Matrix in several languages, including Russian, which is 

the language that many Central Asian scientists speak.

 

Figure 2: Schematic of the Euclid Statistical Matrix

We disseminated our Matrices using a large e-

mail network generated as a part of the Global Health 

Network Supercourse project13. As a part of this project 

we obtained e-mails from top universities in the 

countries/regions of focus and developed region based 

teams of interest. Individuals from the teams of each 

region then developed a message on their matrix and 

distributed it to their local and global colleagues. By 

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TILVES 

 
This work is licensed under a Creative Commons Attribution 4.0 United States License. 

 
This journal is published by theUniversity Library System of the University of Pittsburgh as part  

of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

having team-developed messages, we are better able to 

facilitate international collaboration while also 

promoting these resources from within the regions. Using 

our Iranian team as an example, we distributed the 

information on the Farsi Statistical Matrix to a network 

of over 10,000 Iranian faculty members from top 

universities in Iran. Additionally, we have collaborated 

with an Iranian-American Student Association in the 

US14, where we shared this information among a few 

thousand Farsi-speaking students.  

 Increasing the distribution of information on 

research methods will require multiple tools. In addition 

to the Euclid Statistical Matrices, we are also developing 

matrices with other research methods content, such as 

matrices with focuses on agricultural statistics, 

epidemiology, and big data. Another future project 

includes the development of a Golden Lecture of 

Statistics. The Golden Lecture concept is to provide very 

small PowerPoint presentations of a particular topic so 

that it may be adopted for lectures in any subject. A 

Golden Lecture for “Health” has already been developed 

so that if, for example, a history professor needs a 

resource to discuss what health is but does not have the 

background to do so, they may utilize the Health Golden 

Lecture slides15. In similar spirit, we also plan to develop 

a Golden Lecture for Statistics.  

The Euclid Statistical Matrices are currently 

housed within the University of Pittsburgh Supercourse 

repository, an online collection of health lectures which 

has previously been used to establish scientific social 

networks16. This network reaches to many regions, 

including the Central Asian region where the network is 

over 1,300 individuals17. Further spread of the Statistical 

Matrix concepts can also occur at the meetings of large 

statistical organizations, where current efforts are 

ongoing to collect and ship statistical textbooks to the 

Library of Alexandria in Egypt18. 

The Euclid Statistical Matrices will be most 

beneficial for developing countries in Central Asia, as the 

language barriers and lack of research methods 

specialists are crippling health sciences in this region. 

With a majority of the research intuitions having access 

to the Internet and increasing coverage of the general 

population, the Statistical Matrices are the perfect tool to 

improve knowledge on research methods in Central Asia. 

An important next step in the Central Asian region will 

be to get support from the universities, public health 

schools, and healthcare and education ministries of 

Kazakhstan, Uzbekistan, Tajikistan, Turkmenistan, and 

Kyrgyzstan, due to the strong centralized structure of the 

education system in these countries.   

We suggest that the Matrix model can be a 

useful tool not only for statistics and research methods, 

but also for virtually any course or age group. This may 

be of benefit in the teaching of Science, Technology, 

Engineering, and Mathematics (STEM) courses for 

youth. The Matrices also are quite versatile and can be 

easily adapted. Matrices have the potential to be layered 

into levels, such that a basic course is the foundational 

level, followed by levels of more advanced courses. 

Various additions could be added onto a Matrix, such as 

the incorporation of questions to test how well a learner 

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CENTRAL ASIAN JOURNAL OF GLOBAL HEALTH 
 

 

This work is licensed under a Creative Commons Attribution 4.0 United States License. 
 

This journal is published by theUniversity Library System of the University of Pittsburgh as part  
of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 

 
Central Asian Journal of Global Health 

Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

mastered the topic, or a help desk where a student may 

post questions that can be answered by other students or 

the professor. 

Scientific progress should not be halted because 

of a fear of statistics. Research methods can be learned, 

and with enough comfort to produce better science. 

When bright and passionate individuals place their minds 

and energies together, we can address and mitigate 

problems like Stataphobia. With multilingual tools that 

utilize already-created internet resources such as the 

Euclid Statistical Matrix, we can begin to eliminate the 

issue of Stataphobia worldwide, leading to increased and 

better-quality research as well as global improvements in 

health. 

 

Acknowledgments  

We would like to thank the Library of Alexandria, 
Egypt, for their wonderful support and services. 
Additional thanks go to the other team members involved 
in the development of the Euclid Matrices, including: 
Team Farsi Matrix — Mahdi Aminikhah, 
Vahid Ghanbari, Mehrnoosh Hadadi, Leila Tavakkoli, 
and Ali Ardalan; Team Japanese Matrix — Makoto 
Kaneko, Rieko Mutai, Yuko Nakano, Toshifumi 
Yodoshi, and Masato Matsushima; and Team English 
Matrix — Ismail Serageldin, Francois Sauer, Faina 
Linkov, and Ron LaPorte. 

 

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TILVES 

 
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of its D-Scribe Digital Publishing Program and is cosponsored by the University of Pittsburgh Press. 
 

Central Asian Journal of Global Health 
Volume 6, No. 1 (2017) |  ISSN 2166-7403 (online) | DOI 10.5195/cajgh.2017.283|http://cajgh.pitt.edu 

 
 

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http://iraniansptgh.com/
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https://www.utimes.pitt.edu/?p=41833

	The Euclid Statistical Matrix Tool
	Editorial

