ECO Statistical Network (ECOSTAT) collects various statistical data
of ECO member countries and International Organizations and provides
an environment for data to be saved for responding to any kind of
analytical queries. download tutorial
ECO Key Statistical Indicators (ECOKSI) is a set of the most important
socio-economic indicators of the ECO member countries which
represent mostly significant changes in the socio-economic condition
of the countries within a period of time.
The Project Risk Management Training Workshop for ECO countries was held on 28-31 March 2012 in Ankara, Turkey. The three international organizations, SESRIC, ECO and IRTI/IDB have jointly organized the training program for the ECO members. During the four day workshop, the participants have been trained on the following subject themes: Project Management Cycle, Project Logical Frame, Project Processes and Risk Identification, Risk Management Guidelines for Project Finance including Project Risk Categorization, Project Finance Risk Mitigation, Identification and Analysis of Project Finance Risks. Furthermore, case studies on the Sarney Dam and Water Supply System Project in Iran and the KSK Gas Field Development Project in Uzbekistan have been presented to provide knowledge on Project Risk Management. In the closing ceremony, Dr. Savaş Alpay, Director General of SESRIC, awarded certificates to the participants from Afghanistan, Azerbaijan, Kazakhstan, Kyrgyzstan, Pakistan, Tajikistan and Turkey.
ECO Annual Economic Report 2010
ECO Economic Journal 2010
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Venue : Astana, Kazakhstan The Centre organised a training course on “Statistical Data Analysis” at the Agency of the Republic of Kazakhstan on Statistics on 18-21 July 2011. The Course was provided by Ms. Afsaneh Yazdani, Director General of Office of Statistical Methodology & Sample Surveys at the Statistical Centre of Iran, and was attended by 14 staff members of the Agency of the Republic of Kazakhstan on Statistics. The training course on “Statistical Data Analysis” mainly covered the following subjects: • Data Collection; Presenting and Summarizing Data • Estimating Population Parameters; Parametric and Non-Parametric Tests of Hypotheses (Inferences on One Population) • Introduction to SPSS (Data Management, Tabulation, Graphs) • Parametric and Non-Parametric Tests of Hypotheses (Inferences on Two/More Populations) • Regression Analysis (Correlation; Linear Regression; Multiple Regression) • Sampling Design and Survey Data; Complexity of Analysing Survey Data • Preparing for Survey Data Analysis (Weighting; Non-response Adjustment/Imputation) • Conducting Survey Data Analysis • Issues on Data Quality (Definitions of Data Quality; Sources of Error; Prevention, Detection of the Errors and Remedies) • Data Mining (Brief Introduction to Concepts and Methods)
