Core Statistics (ONLINE LIVE TRAINING)

This event has already happened
Date/time:

Monday 2 March 2026 9:30am to 1:00pm

Location:

Research Informatics Training - Online LIVE Training

About

Description

This award winning course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences.

There are three core goals for this course:

  1. Use R confidently for statistics and data analysis
  2. Be able to analyse datasets using standard statistical techniques
  3. Know which tests are and are not appropriate

R is an open source programming language so all of the software we will use in the course is free.

In this course, we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to linear models and power analyses. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

If you do not have a University of Cambridge Raven account please book or register your interest here.

If for any reason the above links do not work, please email Research Informatics Training Team with details of your course enquiry.

Additional information
  • Our courses are only free for registered University of Cambridge students. All other participants will be charged according to our charging policy.
  • Attendance will be taken on all courses and a charge is applied for non-attendance. After you have booked a place, if you are unable to attend any of the live sessions, please email the Research Informatics Training Team.
  • Further details regarding eligibility criteria are available here.
Target audience
  • Everyone is welcome to attend the courses, please review the relevant policies.
  • This course is included as part of several DTP and MPhil programmes, as well as other departmental training within the University of Cambridge (potentially under a different name) so participants who have attended statistics training elsewhere should check before applying.
Prerequisites

This course requires users to be familiar with the R language. Attending an introductory course Data Analysis in R is definitely advantageous if you do not have a working knowledge of R already. If you are unable to attend a course or do not have sufficient working knowledge of R prior to the Core Stats sessions, please work through the R course materials.

Sessions # Date Time Venue Trainers 1 Mon 2 Mar   09:30 - 13:00 Research Informatics Training - Online LIVE Training Noam Tal-Perry,  Millie Zhou,  Camice J. Revier,  Ilina Moitra 2 Tue 3 Mar   09:30 - 13:00 Research Informatics Training - Online LIVE Training Noam Tal-Perry,  Millie Zhou,  Camice J. Revier,  Ilina Moitra 3 Wed 4 Mar   09:30 - 13:00 Research Informatics Training - Online LIVE Training Noam Tal-Perry,  Millie Zhou,  Camice J. Revier,  Ilina Moitra 4 Mon 9 Mar   09:30 - 13:00 Research Informatics Training - Online LIVE Training Noam Tal-Perry,  Millie Zhou,  Camice J. Revier,  Ilina Moitra 5 Tue 10 Mar   09:30 - 13:00 Research Informatics Training - Online LIVE Training Noam Tal-Perry,  Millie Zhou,  Camice J. Revier,  Ilina Moitra 6 Wed 11 Mar   09:30 - 13:00 Research Informatics Training - Online LIVE Training Noam Tal-Perry,  Millie Zhou,  Camice J. Revier,  Ilina Moitra

 

Objectives

During this course you will learn about:

  • One and two sample hypothesis tests
  • ANOVA
  • Simple linear Regression
  • ANCOVA
  • Linear Models
  • Model selection techniques
  • Power Analyses
Aims

After this course you should be able to:

  • Analyse datasets using standard statistical techniques
  • Know when each test is and is not appropriate
Format

The course is primarily based around computer practicals interspersed with short lectures and presentations used to explain core ideas and principles.

System requirements

Participants must have their own computers to work on and a stable internet connection for the duration of the course. This course will require you to have an up to date installation of R and RStudio on your computer beforehand. Brief installation guides will be provided and support will be available from the tutors during the sessions.

Timetable Session Topics CS1 Simple Hypothesis Testing CS2 Single Categorical Predictor Variables CS3 Single Continuous Predictor Variables CS4 Two Predictor Variables CS5 Multiple Predictor Variables CS6 Power Analysis Registration Fees
  • Free for registered University of Cambridge students
  • £ 65/full day for all University of Cambridge staff, including postdocs, temporary visitors (students and researchers) and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
  • It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
  • £ 65/full day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
  • £ 130/full day for all Industry participants. These charges must be paid at registration
  • Further details regarding the charging policy are available here