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Workshop on “Preparation of Statistical Reports and Visualization by Tableau” 15-17 September 2018- Statistical Research and Training Centre

Workshop on “Preparation of Statistical Reports and Visualization by Tableau” 15-17 September 2018- Statistical Research and Training Centre

The Workshop on “Preparation of Statistical Reports and Visualization by Tableau” was held by Mr. Golamreza Izadi, Director General, Office of Standards and Supervising Statistical Surveys” and Mr. Nosratollah Haghgu, the Statistician of the Statistical Centre of Iran, in the Statistical Research and Training Centre from 15-17 September 2018 for 12 hours.

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Using Bayesian Inference and Prediction Methods to predict Iran's Unemployment Rate

Using Bayesian Inference and Prediction Methods to predict Iran's Unemployment Rate

The increasing challenges on collecting data by traditional ways have necessitated a study for the transformation or updating of survey methods due to the complexities of today's statistical populations. Using other data sources and modeling are some of the ways that can be employed as an alternative to the survey methods or to increase the accuracy of estimates and inferences from traditional surveys. Information sources derived from the past data (such as the past surveys or registered data) are always one of the most important sources of information for this purpose

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Study and Analysis of Unemployment Status in the Nation’s Provinces from 2011-2016

Study and Analysis of Unemployment Status in the Nation’s Provinces from 2011-2016

Labour force can be considered one of the main factors of economic advancement and development. Relying on the capabilities of labour force, the countries are trying to improve their economic conditions. Emphasis and concentration on identifying determinants of supply and demand of labour force in I.R.Iran dates back to the Fifth National Development Plan. In this Plan, the necessity for decreasing unemployment rate at all geographic levels has been emphasized like other Plans.

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Identifying and Controlling Non-response and Measurement Errors of Statistical Surveys

Identifying and Controlling Non-response and Measurement Errors of Statistical Surveys

Non-response and measurement errors are among the most important non-sampling errors in statistical surveys. Calculation of these errors and providing procedures for reduction of them leads to the improvement of survey results and more efficient estimates. Since researches and survey methodologists are trying to find more efficient methods to assess data quality and results of the surveys, identification of the non-response and measurement errors sources and provision of procedures for measuring and reducing these errors are very important in the surveys

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