Three Day Online Biostatistics for the Non-Statistician Training Course –

DUBLIN–(BUSINESS WIRE)–The “Biostatistics for the non-statistician course” training added Offer.

The focus of the seminar is to provide you with the information and skills needed to understand statistical concepts and results related to clinical research and to confidently communicate the information to others.

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

A lot of statistical software is now available for professionals. However, this software is designed for statisticians and can often be daunting for non-statisticians. How do you know if you’re pressing the right button, let alone running the best test?

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

Emphasis is placed on actual statistical (a) concepts, (b) application, and (c) interpretation rather than mathematical formulas or actual data analysis. A basic understanding of statistics is desirable but not necessary.

Seminar includes:

  • certificate

  • PDF copy of the handouts

  • Q/A session

  • 3-day live webinar and statistical analysis plan provided by faculty.

learning goals

  • Understand the statistical portions of most articles in medical journals.

  • Perform simple calculations, especially those that help interpret published literature.

  • Avoid being fooled by silly insights.

  • Knowing which test, when, why and how.

  • Perform simple analysis in statistical software.

  • Communicate statistical results more clearly with others.

Main 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 cannot do

  • Descriptive statistics and measures of variability

Session 2: The Many Kinds of Interpretation

  • confidence intervals

  • p-values

  • effect sizes

  • Clinical vs meaningful significance

Break 10 mins

Session 3: Data Types and Descriptive Statistics

  • Data Levels: Continuous, Ordinal, Nominal

  • Normal distribution and its meaning

  • Graphic representations of data

  • Data transformations, when and how

Break 10 mins

Session 4: Common Statistical Tests

  • Comparative Tests

  • Simple and multiple regression analysis

  • Nonparametric Techniques

questions and answers

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

  • Relative dangers

  • Interpretation of hazard ratios

  • Presentation of KM curves and Cox regression analysis and interpretation

Break 10 mins

Session 3: Bayesian logic

  • A different way of thinking

  • Bayesian methods and statistical significance

  • Bayesian Applications for Diagnostic Tests

  • Bayesian applications in genetics

Break 10 mins

Session 4: Systematic reviews and meta-analysis

  • Why conduct a systematic review and/or meta-analysis?

  • A bit of history and reasoning for systematic reviews and/or meta-analysis

  • terminology

  • Steps to conduct a systematic review

  • Steps to Conduct a Meta-Analysis

Agenda Day 3: Further understanding in clinical research

Session 1: Other tests

  • Nonparametric Tests

  • Check for equivalence

  • Test for non-inferiority

Break 10 mins

Session 2: Performance and Sample Size

  • Theory, steps, and formulas for determining sample sizes

  • Demonstration of sample size calculations using GPower software

Session 3: review of a journal article

  • General steps for article verification

  • Determining the quality of a journal or journal article

  • Looking for limitations (all studies have them)

Break 10 mins

Session 4: Development of a statistical analysis plan

  • Using FDA (for US audiences) or MHRA (for UK audiences) guidelines as a foundation, learn the steps and criteria required to develop a Statistical Analysis Plan (SAP).

  • All participants receive a SAP template

More information about this training can be found at

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