6-Hour Virtual Seminar on Biostatistics for the Non-Statistician

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.

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.

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.

Seminar Agenda:

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

The many ways of interpretation

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

Common Statistical Tests

• Comparative tests
• Regression analysis
• Non-parametric techniques

Bayesian Logic

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

Interpreting Statistics – Team Exercise

• Team Exercise: Review a scientific paper and learn how to Interpret statistical jargon
• Look for reproducibility, transparency, bias, and limitations
• Convey information coherently to non-statisticians

Study power and sample size

• Review of p-value, significance level, effect size
• Formulas, software, and other resources for computing a sample size

Developing a Statistical Analysis Plan

• Using FDA 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

Specialized topics/Closing Comments/Q&A

• Comparing Survival Curves
• Pharmocokinetics/Pharmacodynamics (PK/PD)
• Taking a holistic view to study design and interpretation
• Question and Answer session

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