Training Course on Research Design, Data Management, Analysis and Reporting

Training Course on Research Design, Data Management, Analysis and Reporting

Location: Kigali Rwanda

Dates

RegistRATION

17-21, Jun 2024

https://bit.ly/42LZIlz

26 - 30 Aug, 2024

https://bit.ly/42LZIlz

14 - 18 Oct, 2024

https://bit.ly/42LZIlz

09 - 13 Dec, 2024

https://bit.ly/42LZIlz

Introduction

A sound research is key for the development of knowledge and is imperative for informed decision making. In order to conduct any research, it is important to embrace appropriate research design and methodology. This course will help you develop competence in quantitative and qualitative techniques through hands-on practices in study design, data collection, and management, as well as the analysis, interpretation and reporting. The participants will be exposed to mobile based data collection using ODK, use of statistical analysis software (Ms-Excel, Stata, SPSS, R and NVivo).

Target Participants

The training is designed for participants who intend to learn how to plan, implement effective research studies including data management and analysis.

What you will learn:

By the end of this training the participants will learn to:

• Understand and appropriately use statistical terms and concepts
• Design and Implement universally acceptable research
• Develop of functional research protocol
• Design both quantitative and qualitative data collection tools
• Perform data analysis tasks with Microsoft Excel, Stata, SPSS, R and NVivo
• Perform simple to complex data management tasks using software
• Perform statistical tests using software
• Write reports from survey data

Course Duration

5 Days

Course outline

Statistical/Recap to Statistics Concepts

Statistics concepts

• Types of data (qualitative and Quantitative data)

• Data Analysis Techniques
• Descriptive Statistics and Inferential Statistics
• Common inferential statistics
• The core functions of inferential statistics

Research Methodology

• Research Methodology process.
• Components of research methodology.

Research Design and Data Collection tools & techniques

Research Design

• Definition of research design
• Types of research designs

• Benefits of various research design to a study
• Selecting Appropriate research design (Informed by the scope of a project)
• Potential errors in research and how to prevent them in research planning stage and control
• Exercise: Determination of Appropriate Research Design for a project.

Target Population, Sample Size, and Sampling techniques

• Target population identification
• Sample size determination
• Different types of Sampling techniques, their advantages, and disadvantages and when to use each

Data Collection Techniques and tools for a survey

• Definition of data collection techniques
• Different techniques for data collection, they advantages, and disadvantages
• Tools for data collection
• Designing survey questionnaires (based on study objectives)
• Pretesting research tools for Validity and Reliability

Mobile Based data Collection using ODK and GIS Mapping

• Introduction to mobile phone data collection
• Common mobile based data collection platforms
• Advantages and challenges of Mobile Applications
• Challenges
• Introduction to Open Data Kit ODK
• Components of Open Data Kit (ODK)
• Collecting data using ODK
• GIS Mapping
• Exercise: use of ODK for data collection exercises and GIS Mapping

Data Management and Analysis using statistical Software (Ms-Excel, Stata, SPSS, R and NVivo)

• Introduction to the software

• Data entry, management, and manipulation
• Importing/ exporting datasets

• Defining and labeling data and variables
• Creating, transforming, recoding variables
• Generating new variables
• Creating New datasets, sorting and ordering, and modification
• Quality checks of datasets: Identify duplicate observations
• Merging and Appending data files

Graphic, tabulations and output management

• Introduction to output Management using
• Tabulating data
• Basics of Graphing
• Customizing Graphs
• Exporting graphics and tabulations.

Analysis of survey data using inferential statistics

• Introduction/recap of inferential statistics
• Statistical inference, their applications and underlying conditions for their use
• Measures and tests of association
• Tests of difference
• Hypothesis testing and inference
• Correlation analysis
• Students T test

Regression analysis and making Inferences:

• Types of regression analysis model and their application.
• Generating regression models

• Linear Regression
• Multiple Regression
• Logistic Regression
• Ordinal Regression

Qualitative Data Analysis using NVivo

• Introduction to NVivo
• NVivo workspace
• Uploading qualitative data into NVivo
• Coding and making nodes
• Use of queries
• Project visualization

Report writing for survey findings, Dissemination and Use

• Writing strategies for simple and advanced levels survey reports
• Report structures
• Considerations before writing the report
• Writing a survey report
• Appropriate language use
• Making conclusions and recommendations
• Communication and dissemination
• Decision making based on findings report