Training on Research Design, Data Management and Statistical Analysis using Stata

Module 1: Introduction to Research

• Introduction to research
• Different types of research
• Formulation of research problem statement
• Formulation of research hypothesis
• Case Study: Weak research design leading to unreliable findings
• Practical: Writing a research problem statement and hypothesis

Module 2: Overview of Evaluation

• Evaluation objectives
• Evaluation criteria
• Evaluation questions
• Role of evaluation in programs and projects
• Case Study: Poor evaluation design affecting project accountability
• Practical: Developing evaluation questions and objectives

Module 3: Research Design

• Quantitative research approaches
• Qualitative research approaches
• Designing research for evaluation purposes
• Case Study: Incorrect research design affecting policy recommendations
• Practical: Selecting appropriate research design for a study

Module 4: Sampling Techniques

• Sampling techniques (probability and non-probability)
• Sample size determination
• Sampling errors and bias
• Case Study: Sampling bias affecting national survey results
• Practical: Calculating sample size and selecting sampling method

Module 5: Data Collection Methods & Tools

• Quantitative data collection methods
• Qualitative data collection methods
• Creating evaluation frameworks
• Survey questionnaire design
• FGD guide design
• KII guide design
• Case Study: Poor data collection tools reducing data quality
• Practical: Designing questionnaires and interview guides

Module 6: Research Protocol Development & Mobile Data Collection (ODK)

• What is a research protocol
• Structure of a research protocol
• Mobile data collection introduction
• ODK Build and XLSForm design
• ODK Collect and ODK Aggregate
• GPS and spatial data collection
• Case Study: Mobile data collection improving field survey efficiency
• Practical: Designing and deploying an ODK survey form

Module 7: Data Processing & Stata Introduction

• Data coding, capture, editing, and imputation
• Treatment of outliers
• Introduction to Stata
• Interface and key terminologies
• Data entry and manipulation (merge, split, sorting, missing values)
• Case Study: Data processing errors affecting research conclusions
• Practical: Cleaning and preparing datasets in Stata

Module 8: Basic Statistics & Data Visualization in Stata

• Descriptive statistics for numeric variables
• Frequency tables
• Cross tabulations
• Stub and banner tables
• Graphs in Stata
• Types of graphs and visualization techniques
• Case Study: Using descriptive analysis for health program reporting
• Practical: Running descriptive statistics and generating graphs

Module 9: Statistical Tests, Associations & Regression Models

• One sample, independent, and paired T-tests
• One-way ANOVA
• Chi-square test
• Pearson and Spearman correlation
• Linear and multiple regression
• Logistic and ordinal regression
• Case Study: Using regression analysis to predict program outcomes
• Practical: Running statistical tests and interpreting outputs

Module 10: Longitudinal Analysis, NVivo & Reporting

• Longitudinal data analysis in Stata
• Features of longitudinal data
• Introduction to NVivo
• Coding qualitative data and creating nodes
• Queries and visualization
• Survey report writing and dissemination
• Use of findings for decision-making
• Case Study: Mixed-methods analysis improving policy decisions
• Practical: Producing a complete research report using quantitative and qualitative data