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Thu 16 Feb, Fri 17 Feb, ... Fri 3 Mar 2023
09:30 - 13:00

Venue: Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter)

Provided by: Bioinformatics


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Wed 12 Jul 2023


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Core Statistics using R (ONLINE LIVE TRAINING)

Thu 16 Feb, Fri 17 Feb, ... Fri 3 Mar 2023

Description

This award winning virtually delivered 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.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Target audience
  • Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
  • 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.
  • Please be aware that these courses are only free for registered University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
  • Further details regarding eligibility criteria are available here
Prerequisites

This course requires users to be familiar with the R language. Attending an introductory course Introduction to R for biologists 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

Number of sessions: 6

# Date Time Venue Trainer
1 Thu 16 Feb   09:30 - 13:00 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter) Martin van Rongen
2 Fri 17 Feb   09:30 - 13:00 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter) Martin van Rongen
3 Thu 23 Feb   09:30 - 13:00 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter) Martin van Rongen
4 Fri 24 Feb   09:30 - 13:00 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter) Martin van Rongen
5 Thu 2 Mar   09:30 - 13:00 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter) Martin van Rongen
6 Fri 3 Mar   09:30 - 13:00 09:30 - 13:00 Bioinformatics Training Facility - Online LIVE Training (Time Zone = BST (GMT+1) in Summer, GMT in Winter) Martin van Rongen
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

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. Participants must have their own computers to work on.

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
  • £ 50/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.
  • £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
  • £ 100/day for all Industry participants. These charges must be paid at registration
  • Further details regarding the charging policy are available here
Notes

The course is designed to allow participants to engage with the material either synchronously and asynchronously. After you have booked a place, if you are unable to attend either the live lecture component or the live practical support component of any session then you should still be able to access the course materials and the recordings, which will be made available after each session. If you are unable to attend any of the live sessions, please email the Bioinfo Team as Attendance will be taken.

Duration

3

Frequency

Twice per term

Related courses
Theme
Core skills

Booking / availability