Ako Sauga's homepage

Academic Portfolio

Ako Sauga

I Pedagogical Activity

Teaching Experience

Department of Economics and Finance, Tallinn University of Technology 2007-present
  • Statistics (TES0020), bachelor's programmes;
  • Econometrics (TES1040), master's programmes;
  • Time Series Econometrics (TES9140), doctoral programmes;
  • Econometrics (TES9130), doctoral programmes, until 2013 Fall.
Syllabi, examples of lecture slides, exercises and test papers are available online. Corresponding links are presented in Appendices.

Department of Natural Sciences, Tallinn University

  • Physical Picture of the World, bachelor's programmes;
  • Stochastic Processes, master's programmes.

Faculty of Economics, International University Audentes

  • Economical Mathematics;
  • Business Statistics;
  • Modelling and Optimization;
  • Computer Sciences;
  • Probability Theory for Computer Scientists;
  • Statistics in Social Sciences, master's programmes;
  • Quantitative Methods in Economics, master's programmes.
Teaching and learning materials (lecture notes, exercises) of some courses are available in my homepage www.sauga.pri (in Estonian).

Institute of Physics, Tallinn University of Technology

  • Laboratory of Physics.


20 master's and 17 bachelor's theses have been defended under my supervision since 2007. In addition, I have been a supervisor for 16 research papers in the Core Study. Currently I am supervising one doctoral student; the topic of her thesis is "Economic Growth and Financial System Development in Consolidating and Globalizing Environment".

Teaching Philosophy

I have met many business people who have told me that they would never use statistics because they consider statistics as complicated calculations. In my opinion teaching statistics should motivate people to use statistics in their work and everyday life without any terrifying complexity.

Teaching Methodologies

Learning statistics is impossible without practical data analysis. However, until this year there was no statistics textbook with downloadable data files written and published in Estonian. Nowadays it is not a reader-friendly approach to publish printed data tables so that one must independently enter the data to calculate examples and to solve data analysis problems. This was the main reason to publish my statistics textbook (Sauga, A., Statistika õpik majanduseriala üliõpilastele, 2017, TTÜ Kirjastus, 766 lk). The textbook was published under the programme of the Estonian language textbooks for higher education institutions, funded by the Ministry of Education and Research. The programme supports publishing Estonian study and research literature and the main goal is to develop the scientific terminology of the Estonian language.

The textbook introduces basic statistical methods and their application in solving various business and economic problems. Guidance for the statistical data analysis in Excel and LibreOffice Calc is provided. There are nearly 200 examples in the textbook, most of which can be found in the spreadsheet files attached to the textbook. Example files include calculations and explanatory comments. There are over 400 exercises to be solved independently, about half of which need to be solved in the spreadsheet, using the data from the attached files. All exercises are equipped with answers. The vast majority of the data used in examples and exercises comes from the real life. The sources of data include online databases, scientific publications, published surveys, supervised student works, etc.

I have been using the possibilities of Internet to support my courses since the end of the 90's. At first I made all teaching and learning materials (lecture notes, spreadsheet files) downloadable from my homepage. Later I included some screen videos, made with software Wink. As the feedback about performance and self-assessment are important in the learning process, I learned HTML language and Javascript to design and build quizzes including multiple-choice and true-false questions.

Nowadays there are many e-learning environments, which carry out this kind of tasks. In TUT we use an open-source learning platform Moodle. All my lecture courses are supported by the corresponding e-course in Moodle. There are lecture slides, data files, self-tests, forums and links. For example, the question bank of the Statistics course contains 230 questions in various formats, grouped by the topic. These questions are used to build self-assessment quizzes to help students quickly see what they know and do not know. Wrong answers are provided with comments. There is a quiz after each lecture and students should complete it before the next lecture. This motivates students to study consistently during the semester.

Since my first lectures in statistics I have implemented many different approaches to visualize my teaching. I have used Visual Basic in MS Excel to create interactive plots and calculations, but the possibilities of Excel are somewhat limited and therefore I have also used more advanced approaches. For the past six years, I have used Computable Document Format (CDF) to design different interactive demonstrations. CDF is launched by Wolfram Mathematica (http://www.wolfram.com/cdf/) and it is powerful technology to build presentations that are dynamic and interactive. You can change the parameters, rerun models and present results. Using computer simulations, one can take thousands of samples to illustrate, for example, type I and type II errors in hypothesis testing or biased and unbiased estimators. To view CDF document, one must install Wolfram CDF Player, which is free. All CDF demos (44 in Statistics and 11 in Econometrics) are available on my homepage http://www.sauga.pri.ee/cdf/ (in Estonian, some of them are translated into English). So, students can independently work with these demos to understand the statistics and econometrics concepts. It is a great feeling to experience that a well-done visualization has made the material much clearer and more interesting for students.

Data Analysis Software

Statistics and Econometrics courses both have computer labs in the schedule, but it is important that students have a possibility to deal with practical data analysis independently. Thus, they should have the opportunity to use the suitable software.

In Statistics course we use MS Excel in the computer lab. All TUT students have free access to download and install MS Office in their own computer and thus they can use Excel outside the computer lab too. Their second option is to use freeware LibreOffice. Instructions for the statistical data analysis in Excel and LibreOffice Calc are presented in my textbook.

In Econometrics course for masters students we use econometrics software Gretl (http://gretl.sourceforge.net/). It is free, open-source software and students can download and install it in their own computer. Its main features are: easy intuitive interface, a wide variety of estimators, time series methods, models with limited dependent variables and panel-data estimators. To support students I have written the online user guide for Gretl in Estonian (http://www.sauga.pri.ee/gretl/).

In doctoral courses we use econometrics software Stata and EViews.

Assessment Methods

In assessment I follow mainly the following principles: In Statistics course I use three assessment methods:
  1. A test paper: performing statistical calculations by calculator. Topics are: statistical averages and measures of variation, probability, index numbers.
  2. Students' activities during the semester: participation in computer labs and activity in the Virtual Learning Environment Moodle.
  3. Examination consists of two parts.

The test paper accounts for 20%, student's activity 10% and exam 70% of the final grade.

In the Econometrics course I use the following assessment methods:
  1. A test paper: a quiz (terms, concepts) and a practical problem (evaluation of model parameters, testing, interpretation of results).
  2. Home assignments where students are expected to use some data to set an econometric model, evaluate the parameters, test the model and write a report.
  3. An examination consists of two parts.

After completing the test paper and the exam all students receive an individual feedback in Moodle.

The test paper accounts for 20%, home assignment 25% and exam 55% of the final grade.

II Academic Excellence

Teaching is very important for me and I put a lot of time, energy and emotion in it. I am greatly interested in how effective my efforts have been and therefore I observe the students' feedback every semester, which I find very useful. The average score for the Statistics course (Spring 2016) was 4.58 and the average of Econometrics course (Fall 2016) was 4.9 according to the students' feedback.

Some comments from the Econometrics students in the fall of 2016 (translation from Estonian): Of course, there are additional options to improve the academic excellence.

Individual Development

2018 Course "Introduction to Programming II (Python)", 78 hours, Tartu University, Estonia
2017 Course "Introduction to Programming (Python)", 78 hours, Tartu University, Estonia
2017 Course "About Programming (Python)", 26 hours, Tartu University, Estonia
2013 Course "Learning-based teaching - A Challenge to a Teacher or a Student?", Tallinn University of Technology, Estonia
2010 Course "Learning Object Tools (Adobe Flash)", 65 hours, Tallinn University of Technology, Estonia
1993 Educational Psychology Summer School, Bornholm, Denmark
1988 Course in University Pedagogy, Tallinn University of Technology, Estonia

III Management in the Field of Education

2017 spring Preparing new requirements for student papers and new procedures for supervising, reviewing and defending graduation theses at TTÜ School of Business and Governance, a team member.
2016- Department of Economics and Finance at TUT, member of council
2009-2010 School of Economics and Business Administration at TUT, a member of council
2008-2013 The Head of the Chair of Statistics and Econometrics
2008-2013 Department of Finance and Economics at TUT, a member of council

IV Other

Learning Materials for High School

From 2011 to 2013 I participated in the project which goal was to create teaching and learning materials for the high school mathematics course "Foundations of Mathematical Economics" (project number K103). Our team prepared the materials for 35 academic hours: a textbook, slides and methodical material for teachers, e-course in Moodle.

In 2013 our team won the public procurement to create teaching and learning materials for the other high school mathematics course "Mathematical applications, study of real processes". We prepared the materials for 35 academic hours: textbook, computer based tasks, interactive demonstrations in CDF format, slides and methodical material for teachers and e-course in Moodle.


In summer 2013, I was invited to give a presentation on the Math Teachers' Days. I presented two new sets of learning materials, which were prepared by our team.

In 2011, I was proposed to write some articles for the journal "Raamatupidamise Praktik" ("Accounting Practitioner"). As a result, six articles about the statistical averages, percentage calculation, logarithms, index numbers, present and future value of money and annuity were published.

In April 2007, I received an invitation to lead a workshop in economic analysis for the employees of the Statistics Estonia.

In Nov, 2006 we performed two radio broadcasts with journalist and editor Priit Ennet on the topic "Can noise be useful?".

Teaching Awards

2017 The Dean's letter of thanks for statistics textbook in Estonian.
2014 The best lecturer of TUT.
2014 Estonian e-course quality label to the course "Econometrics TES1040".
2013 The Vice-Rector's letter of thanks for effective and creative teaching.

V Appendices

References to online materials.

Syllabuses of Statistics, Econometrics and Time Series Econometrics

Statistics Econometrics Time Series Econometrics

Interactive demos in Statistics and Econometrics in CDF format.

Software support

Average marks of student surveys.