Long Courses

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

star_full star_full star_full star_full star_full

MODE
Virtual (Google Meet)
TYPE
Self Paced
LEVEL
DURATION
3 Months
VIDEO LENGTH
1

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.

Short Courses 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.

Short Courses Structure

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

Participant’s Eligibility

Graduates, Post Graduates, Research Scholars, Academicians, Industry Professionals of Healthcare and Medical Research Sector

Short Courses 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.


Fee Structure

Batches

Spring
Summer

Autumn
Winter

Certificate

Still have any Query?