Biostatistics for the Non-Statistician, 2019 Seminar –

Virtual Seminar on Biostatistics for the Non-Statistician”

webinar has been added to’s

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.

Why you should attend:

  • 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
  • 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.

Who Should Attend:

  • Physicians
  • Clinical Research Associates
  • Clinical Project Managers/Leaders
  • Sponsors
  • Regulatory Professionals who use statistical concepts/terminology in
  • Medical Writers who need to interpret statistical reports


Lecture 1 (45 Mins) – 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

Lecture 2 (45 Mins) – The many ways of interpretation

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

Lecture 3 (45 Mins) – Common Statistical Tests

  • Comparative tests
  • Regression analysis
  • Non-parametric techniques

Lecture 4 (45 Mins) – Bayesian Logic

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

Lecture 5 (45 Mins) – 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

Lecture 6 (45 Mins) – Study power and sample size

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

Lecture 7 (45 Mins) – 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

Lecture 8 (45 Mins) – 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

For more information about this webinar visit

Laura Wood, Senior Press Manager
E.S.T Office Hours Call 1-917-300-0470
For U.S./CAN Toll Free Call
For GMT Office Hours Call +353-1-416-8900
Topics: Bioinformatics