Data Management and Analysis in Research

Course description and objectives
Data provides the evidence needed to institute change, the role of data in decision making can no longer be undermined. While its need is important and the knowledge and means of obtaining it widely accessible, once we have the data, more often than not, we are at a loss, regarding what to do with it. This course is designed to guide learners on how to manage data, analyze it, and present it to relevant audiences, essentially, transforming data into evidence and ultimately, guiding policy action.

This course has three main objectives:
  • To introduce learners to three main components of data management
  • To help learners to understand and practice data analysis using statistical software
  • To prepare learners to interpret the findings of analyzed data
Course participants will gain insight into the data transition process; from designing data entry pages to presenting the results to audiences. By the end of the course, you will be able to design data entry pages, enter and clean your data, analyze it using appropriate techniques, and interpret your findings/analysis. Throughout the course, learners will conduct practical components of data management and analysis, share progress with others, obtain feedback, and learn from the experiences of peers while working on individual research projects.


This Course is 6 Weeks Online


  • UGX 500,000/-
  • USD 140$


This course is designed for students, healthcare providers, and other users who need to transform their data into actionable evidence, these may include: Data and Monitoring and Evaluation teams from NGOs & University departments, Researchers, Health Care Workers in clinical practice, Public Health Experts, Ministry of Health Officials and leaders in the health sector (both private and public) will benefit from the course.
Content areas
Data Management
1. Designing a data entry page with Epidata and SPSS
2. Exporting Data
3. Data cleaning
Results presentation
1. Graphs and tables
2. Text
3. Interpretation
4. Developing a presentation for audiences
Data analysis
Descriptive statistics
  • Graphical methods
  • The measure of central tendencies + Measures of dispersion
  • Categorical variables
Relational statistics
  • Student t-test
  • Analysis of Variance
  • Chi-Square test
  • Correlation
  • Linear regression
  • Logistic regression

Facilitator's Profile

Ms. Nakaggwa Florence

Florence is an Epidemiologist and Biostatistician with high-level proficiency in data management and analysis using software such as; Surveytogo, Survey 123, Open clinic for data capture, and Microsoft Excel, SPSS, R, and STATA as well as Nvivo for analysis of both qualitative and quantitative data. She also has a certificate in qualitative research methods from the University of Oxford (Health Experiences Research Group). She has worked with national and international partners such as the World Bank, PSI & IDI, managing projects, and large and complex datasets.

Her expertise as a researcher is in Public health particularly maternal and child health, Health Systems Strengthening, and Health Management Information Systems. Florence is a co-author of a primary health care textbook, more than 8 publications (and several in press) as well as a 3- time reviewer of abstracts for the International Conference on Family Planning. Florence is a facilitator of the Introduction to Health Sciences Research module at Clarke International University and supervises both graduate and undergraduate research students.