- Issayas Tesfamariam
A conversation with Prof. Gebrenegus Ghilagaber: Head of the Department of Statistics, Stockholm Uni
Prof. Gebrenegus Ghilagaber, Head of the Department of Statistics, Stockholm University.
Senai Wolde-Ab and Issayas Tesfamariam conducted the interview.
Would you tell us about yourself?
I was raised in Asmara (including Edaga Arbi, Akriya, Geza Banda Habesha, Cherhi and Mai Temenay). I went ‘Enda Yenieta’/ traditional priest school for two years, and then to Abune Tekle-Haimanot school in HazHaz (commonly known as Enda Abatachn) where I completed three grades (2nd to 4th) in two years. This was followed by four years in Agazian Elementary and Junior Secondary school (grades 5-8). After that I was assigned to Luul-Mekonnen (later Asmara Comprehensive) High School in Asmara and spent six years (including two interrupted years) and joined Addis Ababa University in Autumn 1978.
About a semester before graduating with a BSc in Statistics (July 1982) I was recruited by Asmara University as a GA (Graduate Assistant). I went back to Addis Ababa, Ethiopia for a Masters after teaching one year at Asmara University. I returned to Asmara with an MSc in Statistics and worked for three more years (until 1988) as a Lecturer in Statistics. One of my external examiners for the Master’s Comprehensive Exam was a Professor from Uppsala University (Sweden) and, through that connection, I ended up in Sweden. Got my PhLic (Licentiate Degree) in Demography from Stockholm University and PhD in Statistics from Uppsala University. After I worked as an Assistant Professor at a smaller University (University of Skövde), I joined Stockholm University in August 1999 – as Assistant Professor (1999-2002), Associate Professor (2003-2010) and Full Professor and Head (since August 2011).
Through all these years (and until now) football/soccer (both playing and watching) has been my trusted companion.
Note: Prof. Gebrenegus along with his PhD student is writing a report measuring the effects of 3-points-for-a-win (3pfaw) rule in football
/soccer using advanced statistical methods (Bayesian Change-point) to measure that effect which have interesting results. We will ask him about the report once it comes out.
What is statistics?
Depending on the context, the word Statistics may be understood in two ways. It may refer to numerical facts or data - as is the case in everyday use of the word in, for instance, the media.
When talking about Statistics as a scientific area it means a branch of mathematics that deals with the collection, presentation/organization, analysis, and interpretation of data. Often, the goal is to be able to draw conclusions about a population based on information from a sample. I often say statistics is about analyzing data in order to extract the best ‘juice’ out of it.
People associate statistics with advanced countries, but not with developing nations. Their reasoning is that in developing countries, one could not get accurate information (data). How would you respond to that.
If we refer to the first definition of Statistics (as numerical facts or data) then this may be true because developed countries have well developed register systems that record, for instance, vital events (births, deaths, etc…) which, in turn, are used to compute some health and development indicators like fertility and mortality.
However, lack of such data does not imply that Statistics (as a scientific area) is not needed in developing countries. To the contrary, such countries need Statistical Scientists who can develop statistical methods that can generate measures of, say fertility and mortality, from limited or defective data.
So, those who associate Statistics with developed countries mean (implicitly or explicitly) that it is easier to find records on important indicators in developed countries. But, there are also improvements in developing countries where data is being collected through surveys - like the Demographic and Health Surveys (DHS) that are regularly carried out in many developing countries.
On the challenges you had to go through to reach where you are now;
There is a Tigrinya expression: ሕማም ሕርሲ ተረሳዒ (which, I understand, it implies pain/suffering can be forgotten easily if it is out-weighted by the outcome/result) and it is possible I ‘suffer’ of the saying. Another Tigrinya proverb ምስ ህዝብኻ መዓት ዳርጋ ግዓት also means that whatever historical events (especially those which were not conducive to promote education) were shared with my peers and, hence, less felt as they were the rule of the days and applied to all.
With the above ‘limitations/reservations’ I can say that the idea and decision to join a University was a challenge – not due to lack of grade but due to the then prevailing situations (both at an individual and collective level). It was only after an advice and an insistence from people with good intentions that I joined the University. Else, I would have continued at the nursing school I was enrolled during the last year of high school and ended up as a nurse (ኣላይ ሕሙማት as we were called then) in order to support the family (which was, indeed, more urgent at the moment).
To sum it up, though I was doing well at school including matriculation (with prizes while passing most of the grades) family situation could have diverted my attention to taking up one of the then available jobs with pays commensurate to high-school graduates. I owe it to one of my classmates and two thoughtful elder sisters of my friends for persuading and pushing me to join University at a time of hesitation.
Then there was the financial/material limitation as a student, but it didn’t matter much as we were boarded in campus during the academic years. Furthermore, I was working during the summer months.
As for my challenges in Sweden, there were those challenges that are common to all who come to a new place and culture (both socially and academically) and those challenges that are more individual (where you go, who you meet, which support/orientation you get, etc…). In my case, this will be too long and can make up its own chapter (a book). But, this does not mean I was always disadvantaged. In fact, I had some advantages because one of the professors in my host department was my external examiner during my Master’s exam in Addis Ababa and he did all he could to ease my adjustment.
Department of Statistics, Stockholm University, Stockholm, Sweden.
In your observation what are the common characters/ habits/ that Eritreans need to develop/do away with/ in advancing towards the high ends of their academic professions;
Some ‘characters’ to develop/acquire:
· Realise/identify your interest as early as possible
· Identify your ‘social and intellectual circle’ so that you don’t end up in an environment that is not conducive to aspiring higher.
· Eagerness (curiosity) to knowledge and readiness for continuous improvement (lifetime learning)
· Patience and perseverance/tenacity (ጽንዓት)
· Use opportunities appropriately. Some may not come again
· Interpersonal (communication) skills
· Take initiative (remember the saying ‘opportunity dances with those on the dance floor’)
Not sure what to say about ‘characters’ to do away with but one common problem with foreigners (at least many of those who I know here) is what I may call ‘artificial barrier’ by making excuses (ምስምስ) before one has even tried.
It was common to hear here (especially among Eritreans during my arrival) that it doesn’t help to study because (as foreigners) all of us will end up in doing ‘ordinary’ jobs.
Having said this, I am also aware that such advice (as is the case with all advice) are easier to say than to implement. As individuals we differ in our degree of ambition, tolerance to adverse situations, etc..
What are the benefits/challenges/ of the Swedish university system for an academic who wants to advance in the Swedish academic universe?
The benefits are clear – you will have unlimited access to research facilities – as the Tigrinya saying goes “here is the horse, here is the field” "እነሆ ፈረስ ፡ እነሆ ጎልጎል". So, resource is the straight-forward benefit (especially for people who come from places like ours).
Some of the challenges are the language and the educational system (for those who come from places like ours and are used to English).
We hear the word probability in statistics a lot. What is the relationship between statistics and probability? Put differently, does the word probability has different meaning in statistics than its use in everyday word?
My view is that the word probability has the same meaning in statistics as in everyday use. It is a measure of the likelihood that something happens (for instance, how likely it is that it will rain tomorrow may be expressed as “what is the probability that it will rain tomorrow?”). Thus, probability is a quantification of the likelihood that an event of interest occurs and the quantity lies between 0 and 1 (0 for impossible event and 1 for sure/certain event).
Perhaps, its use in statistics can be appreciated better if we recall the goal of statistical analyses as mentioned above - to be able to draw conclusions about a population based on information from a sample. Since the entire population is not encompassed (and it is impossible to do so) statistical conclusions can’t be 100 % certain – and the degree of certainty (confidence level) can be expressed in terms of probability. Another simple example of the use of probability in statistics and decision-making is the following. One wants to decide whether to take/carry umbrella or not when leaving home. To make that decision one would need the probability that it will rain. Further, there are consequences of the actions one takes - to be wet (if you don’t take umbrella and it rains) or carry it for nothing (if you take umbrella
and it doesn’t rain). Thus, the decision one takes is a combination of actions, probabilities, and consequences (and, of course, individuals’ propensity to take ‘risk’). This is, of course, very simple example but I hope it can help as a benchmark for thinking of the use of probability in more complex decision situations.
On the relationship between statistics and big data?
Big data refers to complex and voluminous information such as those produced rapidly by modern devices like internet, mobiles, camera, etc.. In my view, such data pose new challenges to professional statisticians as they will have to adjust traditional methods or develop new methods that are better suited to handle the new features of big data.
During the 1950s and 1960s statisticians and demographers were developing methods of estimating vital rates in the light of lack of data (or defective data) – especially in the developing world. Such methods, known as ‘Indirect Methods’ were much used by the United Nations to estimate fertility and mortality rates in developing countries (simply because there were no reliable census or survey data).
Now, the challenges become on how to handle abundant data and make maximum use of it. Perhaps, you may relate it to the challenges one has to deal with (and policies one has to devise) at times of drought and at times of flood – which allows me to add one more Tigrigna saying: ገሊኡ ብማይ፥ ገሊኡ ሰኣን ማይ.
Prof. Gebrenegus, thank you for your time.
For Prof. Gebrenegus' book entitled Advanced Techniques for Modelling Maternal and Child Health in Africa, check the link below.