Mastering Data Management and Analysis: From Collection to Insights
Data management, Data analysis, Data processing,Data integration, Data transformation, Statistical analysis, Data quality assurance, Data governance, Database management, Data architecture, Data interpretation
About Program:
Aim: This program aims to equip participants with the skills and knowledge required for effective data management and analysis in clinical research. Participants will learn best practices for data collection, validation, cleaning, analysis, and interpretation, enabling them to generate meaningful insights and contribute to evidence-based decision-making.
Program Objectives:
- Understand the principles and standards of data management in clinical research.
- Learn best practices for data collection, validation, cleaning, and database design.
- Gain proficiency in statistical methods for analyzing clinical research data, including descriptive statistics, hypothesis testing, and regression analysis.
- Develop skills in using statistical software for data analysis and visualization.
- Learn techniques for interpreting research findings, presenting data effectively, and generating evidence-based insights.
What you will learn?
Week 1: Introduction to Data Management in Clinical Research
- Overview of data management processes and roles
- Importance of data quality, integrity, and security
Week 2: Data Collection and Case Report Form (CRF) Design
- Designing data collection tools and CRFs
- Data validation and quality control strategies
Week 3: Electronic Data Capture (EDC) Systems
- Introduction to EDC systems and their benefits
- Implementation and utilization of EDC systems in clinical trials
Week 4: Data Entry and Cleaning
- Data entry processes and quality control
- Cleaning and validation of clinical research data
Week 5: Database Design and Query Management
- Principles of database design and organization
- Query management and resolution in clinical databases
Week 6: Data Monitoring and Quality Assurance
- Implementing data monitoring and quality assurance processes
- Risk-based monitoring and source data verification
Week 7: Data Analysis Planning and Statistical Considerations
- Planning data analysis and selecting appropriate statistical methods
- Sample size determination and power calculations
Week 8: Descriptive and Inferential Statistics
- Descriptive statistics for summarizing and presenting data
- Inferential statistics for hypothesis testing and estimation
Week 9: Data Visualization and Graphical Presentations
- Techniques for effective data visualization
- Creating graphs and figures for research presentations
Week 10: Statistical Software for Data Analysis
- Introduction to statistical software (e.g., R, SAS, SPSS)
- Data manipulation, analysis, and visualization using statistical software
Week 11: Interpreting and Reporting Research Findings
- Interpreting statistical results and drawing meaningful conclusions
- Reporting research findings in scientific papers and presentations
Week 12: Data Sharing and Secondary Analysis
- Ethical considerations in data sharing and secondary analysis
- Reproducibility and open science in clinical research
Intended For :
Graduates, Post Graduates, Research Scholars, Academicians, Industry Professionals of Healthcare and Medical Research Sector
Career Supporting Skills
Program Outcomes
- Competence in data management principles and best practices in clinical research.
- Proficiency in data collection, validation, cleaning, and database design.
- Skills in statistical analysis and interpretation of clinical research data.
- Ability to use statistical software for data analysis and visualization.
- Proficient presentation of research findings and evidence-based insights.
