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Course Details

Course Title

Statistics for Non-Statisticians

Course Format

One or two day classroom course with a mix of presentations and workshop sessions

Learning Objectives

Statistics are widely used in clinical trials from the design stage and sample sizing through to the analysis and reporting. This course provides an easy to understand explanation of the various statistical terms you will come across and enables you to communicate effectively with statisticians.

Who is it for?

The course has previously been delivered for

  • CRAs/Project Managers
  • Regulatory Staff
  • Marketing & Sales Teams in Pharma Companies
  • Medical Advisers
  • Medical Communication Professionals

The course has also been tailored for specific therapeutic areas including oncology, respiratory, tissue engineered products and vaccines.

Course Content

Data Types & Summarising Data 

  • Different types of data
  • Summarising groups of data
  • Standard deviation, standard error, least square means
  • Confidence intervals and interpretation

Summarising Data – Discrete Data 

  • Odds Ratio
  • Relative Risk
  • Absolute Risk
  • Difference in proportions
  • Number needed to treat
  • Number needed to harm

Summarising Data – Time to Event Data (survival) 

  • Hazard Rate & Hazard Ratio
  • Kaplan-Meier Estimates & Plot
  • Median Time to Event
  • Censoring
  • Proportional Hazards

Summarising Data – Continuous Data 

  • Difference in Means
  • Ratio of means
  • Non-parametric tests

Hypothesis Testing 

  • Hypotheses to test
  • What is a p-value?
  • Statistical tests and p-values (incl logistic regression, chi-squared, Fisher, t-test, ANOVA, log rank, Kaplan-Meier)
  • Statistical Significance versus Clinical Significance
  • Equivalence & Non-Inferiority
  • Interpreting trial results
  • Exercise: Interpreting results

Power & Sample Size 

  • Definition of Power
  • Factors involved in sample size
  • How to sample size
  • How to reduce sample size when population is limited
  • Exercise: Hands-on experience of sample sizing

Analysis Populations 

  • What is an analysis population
  • Intention-to-treat, FAS, All Randomised, Per Protocol
  • Statistical Analysis Plans
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