Training and Capacity Building

This course introduce parsticpnats to STATA softaware, data management using STATA and perform discriptive statistical anaysis of quantitative data.  It is a 48 hour course to be delvered in six days.

Indicators for monitoring and evaluation of programs are markers of program functionality indicating the status of a broader phenomenon that most of the time cannot be directly measured. They are expected to coherently vary with the functionality of a health system and/or health status of people thus allowing health managers understand changes in the health needs of populations and effectiveness of existing interventions.

Monitoring and evaluation plays a critical role in ensuring program effectiveness and facilitating organizational learning. Understanding the basic concepts of monitoring and evaluation helps program implementers, managers, and funding agencies to effectively engage in decision regarding what aspects of their programs get measured, how they are measured, and how findings are used to inform decisions. This course familiarizes participants with the basic concepts of monitoring and evaluation.

R is a powerful language for data analysis, data visualization, machine learning, programming and advanced statistics. Originally developed for statistical programming, it is now one of the most popular languages in data science and statistical analysis. In this course, you'll be learning about the basics of R, and you'll end with the confidence to start writing your own R scripts.

At the end of the course/training, trainees will be able to:

This course will enable parsticipnats to syntesize and generate summary measure from existing litrature to assist practisioners and policy makers to make evidence based decissions.  It is a 24 hour course to be developed in three days. Eligible participants are those who have conducted systematic review and who are at a stage of conducting meta analysis or thow who have completed a systematic review course and they feel that their systematic review will require meta-anaysis.

Programs and projects are funded with the assumption that they will achieve improvements in social conditions promised in the form of goals and objectives. While measuring the status of social conditions targeted by most programs seems straight forward, linking observed states of outcomes with specific programs or projects requires complex designs. This course discusses alternative design options to address the challenges of outcome and impact evaluation.