Dublin, April 29, 2026 (GLOBE NEWSWIRE) -- The "Biostatistics for Non-Statisticians: A Practical Guide (May 26th - May 28th, 2026)" training has been added to ResearchAndMarkets.com's offering.
Built for non-statisticians, designed specifically for professionals with little or no statistical background and helps you confidently work with statisticians and data teams.
The objective of this seminar is to provide every trainee with the information and skills that are mandatory to comprehend numerical concepts and answers as smears to scientific study and to positively convey the information to others.
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.
What Makes This Training Different?
- Practical, Not Mathematical
- No heavy formulas
- No advanced math required
- Focus on real-world application
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
Who Should Attend:
- Physicians
- Clinical Research Associates
- Clinical Project Managers/Leaders
- Sponsors
- Regulatory Professionals who use statistical concepts/terminology in reporting
- Medical Writers who need to interpret statistical reports
- Clinical research organizations, hospitals, researchers in health and biotech fields.
- Persons working in the medical or health sciences, pharmaceutical and or nutraceutical industries, clinical trials, clinical research, and clinical research organizations, physicians, medical students, graduate students in the biological sciences, researchers, and medical writers who need to interpret statistical reports.
Agenda
Day 1: Foundations of Statistics (Build Your Core Understanding)
Session 1: Why Statistics Matters
- Do we really need statistical tests?
- Sample vs. Population - understanding the difference
- What statistics can and cannot do
- Descriptive statistics & variability explained simply
Session 2: Interpreting Results with Confidence
- Confidence intervals demystified
- Understanding p-values (without confusion)
- Effect sizes and why they matter
- Clinical vs. meaningful significance
Session 3: Types of Data & Descriptive Analysis
- Continuous, Ordinal, and Nominal data
- Normal distribution and why it's critical
- Graphical data representation
- When and how to transform data
Session 4: Common Statistical Tests (Practical Overview)
- Comparative statistical tests
- Simple & multiple regression analysis
- Non-parametric techniques
- Live Q&A Session
Day 2: Advanced & Applied Statistical Methods
Session 1: Logistic Regression Made Simple
- When and why to use logistic regression
- Interpreting odds ratios clearly
- Presenting and explaining results
- Working with contingency tables
Session 2: Survival Analysis & Cox Regression
- Key concepts and terminology
- Kaplan-Meier curves & Log-Rank tests
- Proportional hazards explained
- Interpreting hazard ratios
- Presenting survival analysis results
Session 3: Bayesian Thinking
- A new way to interpret data
- Bayesian vs traditional statistics
- Applications in diagnostic testing
- Use cases in genetics
Session 4: Systematic Reviews & Meta-Analysis
- Why they are critical in research
- Key terminology and concepts
- Step-by-step systematic review process
- Conducting a meta-analysis
Day 3: Clinical Research & Real-World Application
Session 1: Specialized Statistical Tests
- Non-parametric methods
- Equivalency testing
- Non-inferiority testing
Session 2: Power & Sample Size (Make Your Study Valid)
- Key theory and calculation steps
- Determining appropriate sample size
- Hands-on demo using G*Power software
Session 3: Reviewing Scientific Literature
- How to critically review journal articles
- Assessing quality and credibility
- Identifying study limitations
Session 4: Developing a Statistical Analysis Plan (SAP)
- Step-by-step SAP development
- Aligning with regulatory expectations from FDA and MHRA
- Key components of a robust SAP
- Ready-to-use SAP template provided
For more information about this training visit https://www.researchandmarkets.com/r/9xpova
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