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.
The goal of this seminar is to teach you enough statistics to:
  • 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.
  • Physicians
  • Clinical Research Associates
  • Clinical Project Managers/Leaders
  • Sponsors
  • Regulatory Professionals who use statistical concepts/terminology in reporting
  • Everyone 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.