Ethiopian Statistical Association (ESA) has organized a number of statistical software and short-term courses for members and various stakeholders through virtual and face-to-face. Obviously, ESA has a strong mission to introduce and promote the newly produced statistical software and cross-cutting short courses for members and potential stakeholders.
Upcoming-> MSc. in Statistics
Dear All,
The Department of Statistics at Addis Ababa University will commence offering an Master of Science Degree in Statistics (MSc. in Statistics) with a new area of concentration in Actuarial Statistics by the coming academic year (2017 EC). We are sharing this information with you in case you are interested in applying or know someone who might be.
You may find detailed information about program admission by following the link below.
Academic Program List – Addis Ababa University (aau.edu.et)
Ethiopian Statistical Association
Ongoing Trainings
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Short Course: Introduction to Statistical Meta-Analysis
Date: August 5 – 8, 2024
Time: Morning, 10:00 – 12:00
Professor Yehenew G. Kifle
Department of Mathematics and Statistics
University of Maryland Baltimore County
Maryland, USA
This short course provides a comprehensive introduction to Statistical Meta-Analysis (SMA), a powerful method for quantitatively combining results from different studies on the same outcome of interest.
Key topics include:
- Standard measures of effect size (means, proportions, odds ratios, and correlations),
- Methods for combining individual tests based on P-values,
- Techniques for pooling individual effect size estimates to determine a common effect size and construct confidence intervals,
- Tests for homogeneity of effect sizes,
- Fixed-effect and random-effects models for meta-analysis,
- Addressing publication bias, and
- Meta-regression with one or multiple covariates.
Throughout this short course, R statistical software will be used for practical applications and analysis. This course is ideal for biomedical researchers and statisticians looking to enhance their skills in conducting and interpreting meta-analyses.
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Instructor: Nicola Gnecco
Visiting Postdoctoral Researcher
Gatsby Computational Neuroscience Unit, UCL, London
Course Dates: June 18, 19, and 20, 2024
Time: 11:00 AM to 1:00 PM (Ethiopia Time)
Course Description
This course provides an in-depth exploration of multivariate analysis techniques with a focus on unsupervised learning methods. The course covers Clustering, Principal Component Analysis (PCA), Autoencoders, and Variational Autoencoders (VAE), providing theoretical foundations, practical applications, and hands-on examples.
Class Schedule
Class 1: Clustering
Topics Covered:
• Introduction to Clustering
• K-means Clustering
• Hierarchical Clustering
• Practical Applications of Clustering
Learning Outcomes:
• Understand the concept and importance of clustering in unsupervised learning.
• Learn various clustering methods and their applications.
• Evaluate and interpret clustering results.
Class 2: Principal Component Analysis (PCA)
Topics Covered:
• Intuition behind PCA
• PCA for data compression and data interpretation
• PCA formal derivation
• PCA using Singular Value Decomposition (SVD)
• Practical applications of PCA
Learning Outcomes:
• Grasp the concept and mathematical formulation of PCA.
• Apply PCA for data compression and interpretation.
• Perform PCA using SVD.
Class 3: Autoencoders and Variational Autoencoders (VAE)
Topics Covered:
• Autoencoders: Architecture and Functioning
• Linear vs. Non-linear Autoencoders
• Introduction to Variational Autoencoders
• Comparison between Autoencoders and VAE
• Practical Applications of Autoencoders and VAE
Learning Outcomes:
• Understand the architecture and functioning of autoencoders and VAEs.
• Differentiate between linear and non-linear autoencoders.
• Apply autoencoders and VAEs for dimension reduction and data reconstruction.
• Compare and contrast autoencoders and VAEs.
Additional Information
We will use R and RStudio to perform hands-on exercises during the lectures. Access to these tools and a laptop during the lectures is not mandatory. However, if you would like to try coding along with the demonstrations, it would be helpful to have a computer with these tools already installed. The exercises will help reinforce the concepts discussed and provide practical experience with the techniques covered in the course.
Downloading and Installing R:
• Visit the Comprehensive R Archive Network (CRAN) at https://cran.r-project.org/.
• Choose the appropriate version for your operating system (Windows, macOS, or Linux).
• Follow the installation instructions provided on the website.
Downloading and Installing RStudio:
• Visit the RStudio website at https://www.rstudio.com/products/rstudio/download/.
• Download the free RStudio Desktop version suitable for your operating system.
• Follow the installation instructions provided on the website.
Training provided by ESA
ESA had organized Statistical Machine learning software training for members. The 2nd Virtual Lecture organized by the Ethiopian Statistical Association during March 06 – 08, 2024 by Prof. George, Oslo University, Department of Biostatistics, Institute of Basic Medical Sciences, Norway. The training was three hours per day total 9 hours. This short course focuses on prediction with high-dimensional input data. What we predict may for example whether or not a therapy given to a patient is successful (binary or categorical outcomes), bone mineral density (continuous outcomes) or survival after cancer surgery (time-to-event outcomes). The prediction is based on high-dimensional input data, for example, thousands of genes in addition to other demographic and clinical variables. There are many methods which can be used to predict outcomes from data in a p>n setting. The method focus was on penalized methods (lasso, ridge and elastic net), boosting, random forests and other ensemble methods.
About 79 members and other stakeholders were invited for free (ESS – 6) were participated and successfully accomplished. The registration fee for ESA members was ETB 300.
Advanced Stata face-to-face Training to employees of TechnoServe Company was given by Dr. Merga Belina and Dr. Habte Tadesse for two days (8 hours a day) during December 18-19, 2023. Then, trainees were certified for participation.
ESA had organized longitudinal data analysis lecture – virtual 1 training for members and stakeholders during November 13 – 14, 2023 by Prof. Peter Diggle, Lancaster University, Lancaster medical school, Lancaster, UK. More than 80 members for two days total 6 hours participated the virtual training. Also ESA Executive Committee members #8, from AHRI #2 and ESS #10 for free were invited. The payment was for free to members but pay a registration fee of ETB 250.
The training was organized to ESA members during May 06 – 13, 2023. The training was virtually given to 28 ESA members by dedicated ESA members, by Mr. Anteneh Tessema, Mr. Diribesa Tsegaye and Mr. Yebelay Bereile, A registration fee of ETB 250 paid for certification and administration overhead.
- Kobo Toolbox Training
Kobo Toolbox training was given to Helvetas Ethiopia 21 staffs from head office and from branch offices. The purpose of this training was to build up the capacity of MEAL staff on digitalization of data collection to be more institutionalized and skilled up to a high standard. Mobile Based Data Collection using Kobo Toolbox has been acknowledged worldwide by researchers, practitioners’ non-governmental organizations, and humanitarian agencies, as very useful and convenient data collection methods – substituting previously used paper-based data collection methods. This training has provided the trainees with the ability to apply the required skills and resources on mobile-based data collection system Kobo Toolbox software.
The training was conducted by Dr. Dejen Tesfaw and Mr. Gezahegn Getahun for five days during December 26 – 30, 2022. Trainees were then certified for completion.
- Power BI Training
The purpose of this training was to build up the capacity of MEAL staff of Helvetas Ethiopia on data visualization. This training was aimed to introduce participants with the basic features of Power BI where the trainees can describe the features of Power BI, see how Power BI works and looks from the users perspective, perform data modeling and visual data.
The training participants/trainees have developed their skill through learning continues training including on job training, experience, innovative/creative and transforming knowledge in to action through practice. All this was done during training conducted by Dr. Taddesse Kassahun and Dr. Zeytu Gashaw. The training was given May 08 – 12, 2023 for 10 of their head office staffs only.
Both trainings were given to ESA members on a virtual basis continuously; Kobo Toolbox from March 21 – 25, 2023 number of trainees’ equal 44 and from March 27 – April 01, 2023 the total number were 52 by the same trainers as above. Registration fee was each ETB 500 and trainees were certified for accomplishment.
The Ethiopian Statistical Association (ESA) has successfully delivered Kobo Toolbox (Digital Data Collection Tool) and Power BI (Data Visualization Software) for the Ethiopian Statistical Service (ESS) in four rounds from September 18, 2023 to October 13, 2023 targeting senior management, core directorate directors, senior statisticians from head quarter, managers of 25 branch statistical offices and statisticians from 25 branch statistical offices.
Overall, a total of 140 participants were participated and certified for both Kobo Toolbox and Power BI training. Each group was trained five days of Kobo Toolbox and Power BI. The Kobo Toolbox training was conducted by Dr. Dejen Tesfaw and Mr. Gezahegn Getahun while Dr. Taddesse Kassahun and Dr. Zeytu Gashaw gave Power BI training.
- Online Data Collection Tools
As we all known, Data collection and monitoring and evaluation (M&E) have always been integral parts of development work. In the past, these tasks were performed with paper and pen, which made them prone to error, difficult to conduct on a large scale, and high in transaction costs. Information and communication technology tools, including hardware like mobile phones and tablets, applications with the capacity to create digital surveys, and software that allows users to upload data to storage facilities in real-time, have reduced the conventional challenges associated with remote data collection. Kobo Toolbox is among many others online data collection software. It is an intuitive, powerful, and reliable software used to collect, analyze, and manage data for surveys, monitoring, evaluation, and research.
All those who have presented and fully attended the designed training program were certified. Memorable pictures of the training are enclosed below.
2. Data Visualization Tools
Nowadays, the concept of data visualization is becoming more popular due to the fact that Data visualization can change not only how you look at data but how fast and effectively you can make decisions. More importantly, it is – analyzing complex data, identifying patterns, and extracting valuable insights. Simplifying complex information and presenting it visually enables decision-makers to make informed and effective decisions quickly and accurately. With this end, various data visualizations tools are produced and most of them are freely available for public. There are a host of third-party visualization tools available to anyone with a web browser. The lists are enclosed below. Tableau Public, Tableau Gallery, Microsoft Power BI, Google Data Studio, Openheatmap, Leaflet Datawrapper, Chartbuilder, Information is Beautiful and Open Refine.
Among the aforementioned data visualization tools, ESA gave training on Microsoft Power BI for ESS staff. Power BI is a very powerful data visualization and business analytics tool provided by Microsoft. It helps to provide interactive visualizations, dashboard & BI Reports with self-service capabilities.