Enables Life Scientists to Understand the Purpose and Uses of Classical Statistics as an Integral Part of the Scientific Method


Topics Covered:

  • Good experimental design and sources of bias.
  • Systematic versus random error.
  • The distinction between samples and populations.
  • The most appropriate ways to describe samples.
  • Estimation and the principle of hypothesis testing.
  • The Standard Error of the Mean and confidence intervals.
  • Understanding and reporting uncertainty.
  • Power, Type I and type II errors.
  • Standard parametric tests and their interpretations, including p-values, test statistics and associated distributuions.

Our Teaching Approach:

  • Emphasises hands-on learning using custom interactive web apps that demonstrate statistical concepts in real-time.
  • Uses in-class exercises and quizzes to reinforce student understanding.
  • Implements a single story-line throughout the workshop allowing students to see how statistics is involved at every step of the scientific method

Science Craft’s Distinctive Advantage:

  • A reference book written for the specific needs of life scientists who have little or no experience with using and understanding statistics.
  • Workshop material developed in collaboration with a statistician currently active in research.
  • Interactive web apps and video animations developed specifically for the workshop complement specific topics in the workshop.

The t distribution, another key distribution in classical statistics, is discussed in context.
Course Details
Duration: 2-3 full days
Maximum Capacity: 12 participants with one (or two) instructor(s)
Instructors: Dr. Rick Scavetta and/or Dr. Irina Czogiel


Click on the arrows to see more feedback. [testimonialswidget_list limit=5 category=statistical-literacy disable_quotes=true random=true hide_title=true hide_email=true hide_url=true hide_location=true hide_company=true hide_datePublished=true hide_dateModified=true hide_name=true enable_schema=”false”]   [maxbutton id=”17″]   [maxbutton id=”18″]   [maxbutton id=”19″]



Concepts in linear regression are explained with simple and easy-to-understand examples and visuals.