Course Outline

Module 1: Introduction/Recap to Qualitative and Quantitative Research and Statistical Concepts

• Definition of qualitative and quantitative research
• Types of Quantitative and Qualitative Data
• Sources of Quantitative and Qualitative data
• Qualitative vs Quantitative
• Descriptive Statistics and common inferential statistics
• The core functions of inferential statistics
• Case Study: Analyzing a mixed-methods research paper to identify the application of qualitative and quantitative research methods and inferential statistics.

Module 2: Introduction to Mobile Phone Based Data Collection Using ODK and Mapping Training

• Introduction to mobile phone data collection
• Components of Open Data Kit (ODK)
• ODK Form (Basic format of XLSForm)
• ODK Collect Application Interface
• ODK Aggregate
• ODK Manage
• ODK platforms and formats
• Downloading and install ODK Collect into mobile devices or using APK file
• Creating ODK Collect Forms
• ODK build;
• Designing and creating Forms
• Designing forms directly on: ODK Build, Koboform builder, PurcForms
• Practical Component: Deploying a mobile data collection survey in the field using ODK and analyzing the collected data.

Module 3: Data Entry, Management, and Manipulation using Stata

• Overview of Stata
• Defining and labeling data and variables
• Creating, transforming, recoding variables
• Generating new variables
• Data Entry, Exploring, modification.
• Transferring data to/from Stata
• Merging and Appending Stata data files (e.g. Excel, SPSS)
• Practical Component: Conducting data cleaning and management on a real-world dataset using Stata.

Module 4: Output Management

• Output Management
• Tabulating data with Stata
• Practical Component: Generating and managing a comprehensive output file for a given dataset, including tables and summary statistics.

Module 5: Stata Graphics

• Basics of Graphing
• Customizing Graphs
• Advanced graphing
• Exporting a Stata graph
• Practical Component: Creating and exporting advanced custom graphs to visualize key trends in a dataset.

Module 6: Quantitative Data Analysis (Inferential Analysis Techniques) using Stata and Reporting

• Statistical Inference
• Regression analysis
• Correlation
• T Test
• Reporting
• Case Study: Conducting a full inferential analysis on a dataset using Stata, including regression, correlation, and hypothesis testing, and preparing a report of the findings.

Module 7: Getting Started with NVivo

• NVivo key terms
• The NVivo Workspace
• Creating a new project
• Opening and Saving project
• Working with Qualitative data files
• Importing Documents
• Practical Component: Setting up an NVivo project with real qualitative data, including document importation and initial project structuring.

Module 8: Working with Codes and Nodes

• Type of Nodes
• Creating nodes
• Browsing Nodes
• Creating Memos
• Memos, annotations, and links
• Creating a linked memo
• Practical Component: Coding and analyzing qualitative data using NVivo, including the creation of nodes and memos.

Module 9: Summarizing the Data

• Creating Attributes within NVivo
• Importing Attributes from a Spreadsheet
• Getting Results; Coding Query and Matrix Query
• Practical Component: Conducting a coding query and matrix query on a dataset and summarizing the findings using NVivo.

Module 10: Visualizing Project

• Displaying data in charts
• Creating models and graphs to visualize connections
• Creating reports and extracts
• Practical Component: Developing visual representations and models of qualitative data connections and relationships in NVivo, followed by generating a comprehensive report.