The "Biostatistics for the Non-Statistician Training Course (Oct 22nd - Oct 24th, 2025)" training has been added to ResearchAndMarkets.com's offering.

Learn Biostatistics for the Non-Statistician

The focus of the seminar is to give you the information and skills necessary to understand statistical concepts and findings as applies to clinical research, and to confidently convey the information to others.

Statistics is a useful decision making tool in the clinical research arena. When working in a field where a p-value can determine the next steps on development of a drug or procedure, it is imperative that decision makers understand the theory and application of statistics.

Many statistical softwares are now available to professionals. However, these softwares were developed for statisticians and can often be daunting to non-statisticians. How do you know if you are pressing the right key, let alone performing the best test?

This seminar provides a non-mathematical introduction to biostatistics and is designed for non-statisticians. And it will benefit professionals who must understand and work with study design and interpretation of findings in a clinical or biotechnology setting.

Emphasis will be placed on the actual statistical (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.

Learning objectives

• Understand the statistical portions of most articles in medical journals.
• Do simple calculations, especially ones that help in interpreting published literature.
• Avoid being misled by foolish findings.
• Knowledge of which test when, why, and how.
• Perform simple analyses in statistical software.
• Communicate statistical findings to others more clearly.

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 nutriceutical 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.

Key Topics Covered:

Agenda Day 1: Basics

Session 1: Why Statistics

• Do we really need statistical tests?
• Sample vs. Population
• I'm a statistician not a magician! What statistics can and can't do
• Descriptive statistics and measures of variability

Session 2: The many ways of interpretation

• Confidence intervals
• p-values
• Effect sizes
• Clinical vs. meaningful significance

Break - 10 mins

Session 3: Types of Data and Descriptive Statistics

• Levels of data: Continuous, Ordinal, Nominal
• Normal distribution and it's importance
• Graphical representations of data
• Data transformations, when and how

Break 10 mins

Session 4: Common Statistical Tests

• Comparative tests
• Simple and Multiple regression analysis
• Non-parametric techniques

Q&A

Agenda Day 2: Special Topics

Session 1: Logistic Regression

• When and why?
• Interpretation of odd ratios
• Presentation of logistic regression analysis and interpretation
• Fun with contingency tables

Session 2: Survival Curves and Cox Regression

• History, theory, and nomenclature of survival analysis
• Kaplan-Meier Curves and Log Rank Tests
• Proportional Hazards
• Interpretation of hazard ratios
• Presentation of KM curves and Cox regression analysis and interpretation

Break 10 mins

Session 3: Bayesian Logics

• A different way of thinking
• Bayesian methods and statistical significance
• Bayesian applications to diagnostics testing
• Bayesian applications to genetics

Break 10 mins

Session 4: Systematic Reviews and Meta-Analysis

• Why perform a systematic reviews and/or meta-analysis?
• A bit of history and reasoning for systematic reviews and/or meta analysis
• Terminology
• Steps in Performing a Systematic Review
• Steps in Performing a Meta-Analysis

Agenda Day 3: Further Understanding in Clinical Research

Session 1: Other Tests

• Non-Parametric tests
• Test for equivalency
• Test for non-inferiority

Break 10 mins

Session 2: Power and Sample Size

• Theory, steps, and formulas for determining sample sizes
• Demonstration of sample size calculations with GPower software

Session 3: How to Review a Journal Article

• General steps on article review
• Determining the quality of a journal or journal article
• Looking for limitations (all studies have them)

Break 10 mins

Session 4: Developing a Statistical Analysis Plan

• Using FDA (for the U.S. audience) or MHRA (for the U.K. audience) guidance as a foundation, learn the steps and criteria needed to develop a statistical analysis plan (SAP)
• An SAP template will be given to all attendees

Speakers:

Elaine Eisenbeisz

Owner & Principal

Omega Statistics

Elaine Eisenbeisz is a private practice statistician and owner of Omega Statistics, a statistical consulting firm based in Southern California. Elaine has over 30 years of experience in creating data and information solutions for industries ranging from governmental agencies and corporations, to start-up companies and individual researchers.

Elaine's love of numbers began in elementary school where she placed in regional and statewide mathematics competitions. She attended the University of California, Riverside, as a National Science Foundation scholar, where she earned a B.S. in Statistics with a minor in Quantitative Management, Accounting. Elaine received her Master's Certification in Applied Statistics from Texas A&M, and is currently finishing her graduate studies at Rochester Institute of Technology.

For more information about this training visit https://www.researchandmarkets.com/r/gqkq08

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