Cost: 30000 KES

Duration: Upto 4 Weeks

• Analyze t data by applying appropriate statistical techniques
• Interpret the  statistical analysis
• Identify statistical techniques a best suited to data and questions
• Strong foundation in fundamental statistical concepts
• Implement different statistical analysis in R and interpret the results
• Build intuitive data visualizations
• Carry out formalized hypothesis testing
• Implement linear modelling techniques such multiple regressions and GLMs
• Implement advanced regression analysis and multivariate analysis

• Introduction to the Instructor and Course
• Data & Code Used in the Course
• Statistics in the Real World
• Designing Studies & Collecting Good Quality Data
• Different Types of Data

• Rationale for this section
• Introduction to the R Statistical Software & R Studio
• Different Data Structures in R
• Reading in Data from Different Sources
• Indexing and Subletting of Data
• Data Cleaning: Removing Missing Values
• Exploratory Data Analysis in R

• Quantitative Data
• Measures of Center
• Measures of Variation
• Charting & Graphing Continuous Data
• Charting & Graphing Discrete Data
• Deriving Insights from Qualitative/Nominal Data

• Data Distribution: Normal Distribution
• Checking For Normal Distribution
• Standard Normal Distribution and Z-scores
• Confidence Interval-Theory
• Confidence Interval-Computation in R

•  Hypothesis Testing
• T-tests: Application in R
• Non-Parametric Alternatives to T-Tests
• One-way ANOVA
• Non-parametric version of One-way ANOVA
• Two-way ANOVA
• Power Test for Detecting Effect

• Explore the Relationship Between Two Quantitative Variables
• Correlation
• Linear Regression-Theory
• Linear Regression-Implementation in R
• Conditions of Linear Regression
• Multi-collinearity
• Linear Regression and ANOVA
• Linear Regression With Categorical Variables and Interaction Terms
• Analysis of Covariance (ANCOVA)
• Selecting the Most Suitable Regression Model
• Violation of Linear Regression Conditions: Transform Variables
• Other Regression Techniques When Conditions of OLS Are Not Met
• Regression: Standardized Major Axis (SMA) Regression
• Polynomial and Non-linear regression
• Linear Mixed Effect Models
• Generalized Regression Model (GLM)
• Logistic Regression in R
• Poisson Regression in R
• Goodness of fit testing

• Introduction Multivariate Analysis
• Cluster Analysis/Unsupervised Learning
• Principal Component Analysis (PCA)
• Linear Discriminant Analysis (LDA)
• Correspondence Analysis
• Similarity & Dissimilarity Across Sites
• Non-metric multi-dimensional scaling (NMDS)
• Multivariate Analysis of Variance (MANOVA)

• All our courses can be Tailor-made to participants needs
• The participant must be conversant with English
• Presentations are well guided, practical exercise, web based tutorials and group work. Our facilitators are expert with more than 10years of experience.
• Upon completion of training the participant will be issued with Foscore development center certificate (FDC-K)
• Training will be done at Foscore development center (FDC-K) center in Nairobi Kenya. We also offer more than five participants training at requested location within Kenya, more than ten participant within east Africa and more than twenty participant all over the world.
• Course duration is flexible and the contents can be modified to fit any number of days.
• The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance and other personal expenses.
• Accommodation, pickup, freight booking and Visa processing arrangement, are done on request, at discounted prices.
• One year free Consultation and Coaching provided after the course.
• Register as a group of more than two and enjoy discount of (10% to 50%) plus free five hour adventure drive to the National game park.
• Payment should be done two week before commence of the training, to FOSCORE DEVELOPMENT CENTER account, so as to enable us prepare better for you.

Cost: 1000 USD

Duration: 5 Days

• Develop project results levels
• Design a project using logical framework
• Develop indicators and targets for each result level
• Track performance indicators over the life of the project
• Evaluation a project against the set results
• Develop and implement M&E systems
• Develop a comprehensive monitoring and evaluation plan
• Use data analysis software (Stata/SPSS/R)
• Collect data using mobile data collection tools
• Carryout impact evaluation
• Use GIS to analyze and share project data

• Fundamentals of Results Based Management
• Why is RBM important?
• Results based management vs traditional projects management
• RBM Lifecycle (seven phases)
• Areas of focus of RBM

• Definition of Monitoring and Evaluation
• Why Monitoring and Evaluation is important
• Key principles and concepts in M&E
• M&E in project lifecycle
• Participatory M&E

• Situation Analysis
• Needs Assessment
• Strategy Analysis

• Results chain approaches: Impact, outcomes, outputs and activities
• Results framework
• M&E causal pathway
• Principles of planning, monitoring and evaluating for results

• Indicators definition
• Indicator metrics
• Linking indicators to results
• Indicator matrix
• Tracking of indicators

• LFA - Analysis and Planning phase
• Design of logframe
• Risk rating in logframe
• Horizontal and vertical logic in logframe
• Using logframe to create schedules: Activity and Budget schedules
• Using logframe as a project management tool

• Overview of theory of change
• Developing theory of change
• Theory of Change vs Log Frame
• Case study: Theory of change

• What is an M&E System?
• Elements of M&E System
• Steps for developing Results based M&E System

• Importance of an M&E Plan
• Documenting M&E System in the M&E Plan
• Components of an M&E Plan-Monitoring, Evaluation, Data management, Reporting
• Using M&E Plan to implement M&E in a Project
• M&E plan vs Performance Management Plan (PMP)

• Importance of baseline studies
• Process of conducting baseline studies
• Baseline study vs evaluation

• Process and progress evaluations
• Evaluation research design
• Evaluation questions
• Evaluation report Dissemination

• Different sources of M&E data
• Qualitative data collection methods
• Quantitative data collection methods
• Participatory methods of data collection
• Data Quality Assessment

• Stakeholder's information needs
• Use of M&E results to improve and strengthen projects
• Use of M&E Lessons learnt and Best Practices
• Organization knowledge champions
• M&E reporting format
• M&E results communication strategies

• Importance of gender in M&E
• Integrating gender into program logic
• Setting gender sensitive indicators
• Collecting gender disaggregated data
• Analyzing M&E data from a gender perspective
• Appraisal of projects from a gender perspective

• Sources of M&E data -primary and secondary
• Sampling during data collection
• Qualitative data collection methods
• Quantitative data collection methods
• Participatory data collection methods
• Introduction to data triangulation

• What is data quality?
• Why data quality?
• Data quality standards
• Data flow and data quality
• Data Quality Assessments
• M&E system design for data quality

• Mobile based data collection using ODK
• Data visualization - info graphics and dashboards
• Use of ICT tools for Real-time monitoring and evaluation

• Principles of qualitative data analysis
• Data preparation for qualitative analysis
• Linking and integrating multiple data sets in different forms
• Thematic analysis for qualitative data
• Content analysis for qualitative data
• Manipulation and analysis of data using NVivo

• Introduction to statistical concepts
• Creating variables and data entry
• Data reconstruction
• Variables manipulation
• Descriptive statistics
• Understanding data weighting
• Inferential statistics: hypothesis testing, T-test, ANOVA, regression analysis

• Introduction to impact evaluation
• Attribution in impact evaluation
• Estimation of counterfactual
• Impact evaluation methods: Double difference, Propensity score matching

• Introduction to GIS in M&E
• GIS analysis and mapping techniques
• Data preparation for geospatial analysis
• Geospatial analysis using GIS software (QGIS)

Cost: 2000 USD

Duration: 10 Days

• Project management processes
• Project management knowledge areas
• Formulas, charts, and theories of project management
• Complex project network diagrams
• Formulas for earned value management
• Compare and contrast processes, knowledge areas, theories, and project management best practices
• Use of data analysis softwares(Spss,NVIVO,Stata,Excel,SAS)

• Project management principles
• Project management concepts and principles
• Issues in Development and development frameworks
• Types of communities
• Empowerment and Community development.
• Distribution of development resources
• Designing community projects
• Community involvement in initiating development projects
• Project Cycle management
• Project stakeholder analysis and need analysis
• Influence Mapping
• Implementation and Control
• Managing development stakeholders
• Monitoring and Evaluation Introduction
• Techniques of project monitoring auditing
• Evaluating project management systems and practices
• Designing monitoring indicators and systems
• Community involvement in Projects monitoring
• Coordinating with national bodies, project steering committees, and project staff
• Evaluating social and institutional change
• Measuring results and impacts
• Assessing economic, social and environmental impact
• Monitoring & Evaluation Indicators and Measurements
• Variables and indicators
• The LOGFRAME Approach
• Surveys and Sampling techniques
• Data characteristics and sources
• Appraisal and rapid appraisal techniques
• Conducting surveys and other social studies
• Monitoring & Evaluation Systems and Tools
• Standards in data management
• Organizational issues in managing information and data
• Monitoring and Evaluation Data Analysis and Interpretation
• Determining and presenting data outputs
• Consultative communications with stakeholders
• Developing the Project Performance Audit Report

• All our courses can be Tailor-made to participants needs
• The participant must be conversant with English
• Presentations are well guided, practical exercise, web based tutorials and group work. Our facilitators are expert with more than 10years of experience.
• Upon completion of training the participant will be issued with Foscore development center certificate (FDC-K)
• Training will be done at Foscore development center (FDC-K) center in Nairobi Kenya. We also offer more than five participants training at requested location within Kenya, more than ten participant within east Africa and more than twenty participant all over the world.
• Course duration is flexible and the contents can be modified to fit any number of days.
• The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and a Certificate of successful completion of Training. Participants will be responsible for their own travel expenses and arrangements, airport transfers, visa application dinners, health/accident insurance and other personal expenses.
• Accommodation, pickup, freight booking and Visa processing arrangement, are done on request, at discounted prices.
• One year free Consultation and Coaching provided after the course.
• Register as a group of more than two and enjoy discount of (10% to 50%) plus free five hour adventure drive to the National game park.
• Payment should be done two week before commence of the training, to FOSCORE DEVELOPMENT CENTER account, so as to enable us prepare better for you.

Cost: 2000 USD

Duration: 10 Days