This intensive 3-day virtual biostatistics online course is designed specifically for non-statisticians who need a clear, practical understanding of biostatistics - without getting lost in complex theory.
Led by industry expert Elaine Eisenbeisz, this course focuses on real-world application, helping you confidently understand data, ask the right questions, and avoid common statistical pitfalls.
Statistics is a valuable tool that is good and useful for making decisions in the medical research arena. When employed in a field where a p-value can determine the next steps in the development of a drug or procedure, it is authoritative that choice makers comprehend the philosophy and request of statistics.
Quite a few numerical software is now available to professionals. However, this software was industrialized for geometers and can often be unnerving to non-statisticians. How do you know if you are persistent in the right key, let unaided execution be the best test?
And it will profit specialists who must comprehend and work with study design and clarification of findings in a scientific or biotechnology setting.
Stress will be placed on the real numerical (a) concepts, (b) application, and (c) interpretation, and not on mathematical formulas or actual data analysis. A basic understanding of statistics is desired, but not necessary.
Led by industry expert Elaine Eisenbeisz, this course focuses on real-world application, helping you confidently understand data, ask the right questions, and avoid common statistical pitfalls.
What You’ll Gain from This Live Training
- Comprehensive Course Materials - Access professionally developed presentation slides for future reference and practical application
- Recognized Certificate of Participation - Strengthen your training records and support compliance documentation
- Live Expert Q&A - Get your specific regulatory and real-world challenges addressed directly by the instructor
Understand Data. Interpret Results. Make Confident Decisions
- Built for non-statisticians
- Designed specifically for professionals with little or no statistical background
- Helps you confidently work with statisticians and data teams
WHAT MAKES THIS TRAINING DIFFERENT
- Practical, Not Mathematical
- No heavy formulas
- No advanced math required
- Focus on real-world application
WHAT YOU WILL LEARN
By attending, you will be able to:
- Understand key statistical concepts used in clinical trials
- Interpret p-values, confidence intervals, and significance correctly
- Identify appropriate statistical tests for different scenarios
- Evaluate research findings and avoid misleading conclusions
- Understand sample size, bias, and study design fundamentals
- Communicate statistical results clearly within your organization
- The training focuses on concepts, application, and interpretation - not complex formulas
Statistics is a valuable tool that is good and useful for making decisions in the medical research arena. When employed in a field where a p-value can determine the next steps in the development of a drug or procedure, it is authoritative that choice makers comprehend the philosophy and request of statistics.
Quite a few numerical software is now available to professionals. However, this software was industrialized for geometers and can often be unnerving to non-statisticians. How do you know if you are persistent in the right key, let unaided execution be the best test?
And it will profit specialists who must comprehend and work with study design and clarification of findings in a scientific or biotechnology setting.
Stress will be placed on the real numerical (a) concepts, (b) application, and (c) interpretation, and not on mathematical formulas or actual data analysis. A basic understanding of statistics is desired, but not necessary.
Course Content
Day 1: Foundations of Statistics
Session 1: Why Statistics Matters
Session 2: Interpreting Results with Confidence
Session 3: Types of Data & Descriptive Analysis
Session 4: Common Statistical Tests
Day 2: Advanced & Applied Statistical Methods
Session 1: Logistic Regression Made Simple
Session 2: Survival Analysis & Cox Regression
Session 3: Bayesian Thinking
Session 4: Systematic Reviews & Meta-Analysis
Day 3: Clinical Research & Real-World Application
Session 1: Specialized Statistical Tests
Session 2: Power & Sample Size
Session 3: Reviewing Scientific Literature
Session 4: Developing a Statistical Analysis Plan (SAP)
Speaker
Elaine EisenbeiszWho Should Attend
- Physicians
- Medical Writers who need to interpret statistical reports
- Clinical Project Managers/Leaders
- Clinical Research Associates Sponsors
- Regulatory Professionals who use statistical concepts/terminology in reporting
- Clinical research organizations, hospitals, and researchers in health and biotech fields
- People engaged in the medical sciences, medicinal and or nutraceutical industries, scientific trials, scientific research, and clinical research administrations, physicians, medicinal students, graduate students in the biological sciences, researchers, and medical writers who need to interpret statistical reports.
