Capacity building training on statistical data processing and analysis in Togo

The STATISTICAL TOOLS package was implemented in Togo across two on-site workshops, led by Mr. Wonou Edem Yao, statistician: the first held in November 2022, from the 14^th to the 25^th, the second held in February 2023, from the 20^th to the 24^th.

The training was developed across three modules focusing on data processing and analysis of agricultural survey data and addressed to the technical staff of the institutions in charge of agricultural statistics.

In Togo, six participants of the trainings came from the Directorate of Agricultural Statistics, Information Technology and Documentation DSID Ministère de l'Agriculture, de l'Elevage et du Développement Rural and the other six participants from the Ministry of Agriculture, Livestock and Rural Development, from the Directorate of Aquaculture and Fishery, and from the National Institute of Statistics and Economic and Demographic Studies (INSEED). The female proportion in the audience was 15%. The FAO representative in Togo, Mr.Djiwa Oyetounde also attended the training.

The first session was opened by Mr. Bouwassi, DSID Director who underlined the importance of GSARS capacity-building support to the country given the fact that producing timely and precise agricultural statistics is fundamental for decision-making. He welcomed the participation of the other Ministries in the training, highlighting its importance for good coordination in the National Statistical System.

The first two TOOLS modules implemented in November focused mainly on the production of descriptive statistics, data-cleaning, and data imputation on an agricultural sample survey data set with statistical software. The third module conducted in February dealt with the sampling and estimation process of agricultural survey data with SPSS.

The training placed a particular emphasis on the quality control of survey data by providing solid basics in programming, procedures, and statistical processing techniques to ensure the quality control of agricultural survey data.

The participants expressed their satisfaction with the knowledge gained in the training, allowing them to have achieved the required expertise to analyze, clean, impute, and estimate agricultural survey data, improving the quality of the statistics produced by the national statistical institutions.