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Advanced Monitoring & Evaluation

Strathmore Univ.
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In an era of demanding stakeholders’ expectations regarding financial probity, budgetary transparency and the proven impact value of funded work programs, monitoring and evaluation (M&E) remain one of those aspects of organizational management that is extensively discussed but rarely practised.

This programme entails M&E data processing and setting up of effective M&E systems within organizations.

Programme Benefits

After attending the programme, participants will be able to:

  • Develop a system to collect and compile data
  • Determine an appropriate method of analyzing, presenting and disseminating information to different stakeholders
  • Demonstrate the ability to use the information to identify problems and implement changes
  • Describe and understand the various stages in an M&E system: planning, data collection, making data usable and using data for decision-making to help organizations reflect on and strengthen their plans
Target Audience

The programme is designed for senior managers and all professionals who might have undertaken the basic Monitoring & Evaluation training and need to progress to the advanced level.

Programme Structure
  • Introduction to surveys
  • Developing survey instruments and procedures
  • Questionnaire design
  • Sampling procedures
  • Data gathering
  • Impact evaluations
    1. Defining impact
    2. Why monitor and/or evaluate impact?
    3. Various techniques: randomization, the difference in difference etc.
  • Group discussions

Digital Data gathering (Open Data Kit):

  • Survey Authoring
  • Designing forms manually: Using XLS Forms
  • Hosting survey data and platforms for hosting
  • Configuring the server
  • Preparing the mobile phone for data collection
  • Downloading data
  • Working with Spatial data (GPS Coordinates)

Comparison of Data analysis packages Excel, SPSS, STATA, R etc.

  • Plenary discussion with participants
  • The rationale for choosing software for analysis
  • Qualitative vs. quantitative data
  • Variable selection and analytical needs
    1. Data quality: criteria and cleaning processes in excel/SPSS
    2. Data validation

Introduction to Excel for Data processing and Analysis

  • Data Auditing and Validation using Excel
  • Variable measures: categorical vs. interval
  • Measures of central tendency and association
  • Data visualization in excel: graphs, charts and tables
  • Overview of SPSS
  • Data Management and Graphics with SPSS

Running frequencies in SPSS

  • Tests of significance: comparing groups/area
  • Tests of Association (Cross-tabs, Chi-Squared, Tau, Eta, Phi & Cramer’s V)

Difference (T-Test, Chi-Squared)

  • Analysis of Variance (ANOVA)
  • Correlation Analysis (Pearson, Spearman)
  • Regression Analysis
  • Interpreting data: statistical inference
  • Data for decision making
  • Understanding stakeholder needs
  • Knowledge management

Информация об оплате

KES. 110,000 (tuition, learning materials, certificate, meals, excludes accommodaion)

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