Data Analysis

Course Objectives

Upon successful completion of this course participants should be able to:

Discuss the relevance of reliable data collection process in Research

Design appropriate research instruments

Use relevant computer packages for data management and extrapolation

Link research results to successful policy implementation

To introduce the concepts of monitoring and evaluation and the value of implanting it in programs/projects

To focus participant’s attention on monitoring and evaluation study designs

M&E Data Management and Analysis

To introduce participants to GIS software, data capture methods, analysis, data importation and mapping indicators using GIS Techniques)

Get hands on skills on SPSS

Conduct project Evaluations

Engage in project operational Research

Embrace use of data in informed decision making

 

           Main Modules

Fundamental concepts and tools for monitoring and evaluating programs Advanced Microsoft Excel.

Observational data, quasi-experiments and correlation studies

Social experiments, natural experiments and Randomized control trials Qualitative evaluation designs

Conceptual issues in M&E data Data types and sources Planning data Collection

Selecting study elements (Sampling) ICT tools for Data processing Comparison of Data analysis packages Basic data quality checks

Basic exploratory data analysis procedures

Introduction to Quantitative analysis (Descriptive Summaries, Data Tabulation methods) o Graphing qualitative data Graphing Quantitative data

Performing common inferential statistical test (t-test, correlation, Chi Square, Analysis of variance (ANOVA)

Regression analysis and econometrics

 

Introduction to Geographic Information System (GIS)

Introduction to GIS  Software (Quantum GIS)

Mobile GPS Field Work

Mapping M&E Indicators with Quantum GIS

Participatory Mapping and collective intelligence (Google Maps, Google Earth)

Application and use of STATA

Application/Use of Nvivo

Importing and Coding Documents Importing and coding other items Classifying and Categorizing Data Grouping your data: collections and links Models and relationships

Reporting and presenting your findings.

 

Who Should Attend?

The course is recommended for the following;

Departmental heads

Data manager

Research students

Project or Departmental managers

Project officers

Staffs involved in making informed decision

Anyone involved in development project

Anyone who aspires to be a good manager

Researchers & M&E officers.

Way forward After the Training

Participants will develop a work plan through the help of facilitators that stipulates application of skills acquired in improving their organizations. ASPM will monitor implementation progress after the training.

 

Training Evaluation:

Participants will undertake a simple assessment before the training to gauge knoweldge and skills on  data analysis & management, another assessment will be done after the training in-order to demonstrate knowledge gained through the training.

 

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