Introduction to Statistics

Introduction to Statistics is a course for University of St Andrews research degree students (see eligibility advice below) and staff. The aim of this course is to introduce basic statistical concepts and analysis methods. The focus is practical application of statistics rather than theory and using R/RStudio to implement the methods. The whole course is split into two parts (one part per semester) and participants can do one or both parts.

  The course is facilitated by St Leonard’s Postgraduate College and delivered by the Centre for Research into Ecological and Environmental Modelling (CREEM).

The whole course is spread over semesters 1 and 2 and there will be a guided programme for self-paced study. Course material (lecture notes, exercises and computer practicals) will be available online.

Content and Structure

Semester 1

I – Data collection, types and visual and summaries

II – Probability, statistical distributions, and confidence intervals

Semester 2

III- Hypothesis tests (tests, ANOVA, categorical data)

IV- Regression and linear models

The course includes a substantial practical component and the methods covered will be implemented using the statistical programming environment R and RStudio.  

There will be in-person introductory session to get you started and throughout the course there will be online help sessions, and a final in-person session to finish the course. You are encouraged to attend the introductory and final sessions in-person to meet the tutor and provide feedback. Participation in the help sessions is optional. 

The weekly time commitment is anticipated to be about 2-3 hours (working through the course notes and associated computer practical and attending any help session).

There is an option for participants to obtain a certificate (for each part) by attempting all assessed quizzes and a score of at least 50% obtained for each quiz. See the course timetable for the deadline for submitting responses to the assessed quizzes.


Week Week starting Chapter in notes Material covered
4 02/10/2023 1 Introduction (in person): Thurs 5 October 11am
5 09/10/2023 2 Data collection and sampling
6 16/10/2023 3 Describing data; numerical and visual summaries
7 23/10/2023   Independent Learning Week
8 30/10/2023 4 Probability
9 06/11/2023 5 Discrete distributions and random variables
10 13/11/2023 6 Continuous distributions and random variables
11 20/11/2023 7 Confidence intervals
12 27/11/2023   Final session (in-person): Thurs 30 November 11am
13 04/12/2023    
14 11/12/2023   Final date for completing assessed quizzes at the end of this week


Entry Requirements and Prior Learning

There are no pre-requisites for participants enrolling for Part 1 (semester 1), however knowledge of data collection and data summaries will be required for Part 2. Some prior knowledge of R/RStudio would be helpful but this will be introduced during Part I.

It would be helpful if R and RStudio are installed on your laptop before the course starts; guidance will be provided after enrolling for the course and in the introductory session.


The course is open to University of St Andrews staff and students matriculated on a doctoral degree or the following research degree programmes – MSc (Res), MSt (Res), and MPhil (by research).

The course is not open to students on an undergraduate degree or to students on a taught postgraduate degree programme (MSc, MLitt, or MRes).

Book Your Place

You can enrol on the course through the Personal Development Management System (PDMS). Course code -13892.

If you have questions please contact St Leonard’s Postgraduate College via email [email protected].

Contact us

St Leonard's College
The Old Burgh School,
Abbey Walk
St Andrews
KY16 9LB

[email protected]

Phone:+44 (0)1334 46 2003

Upcoming events

EndNote:an introduction
Thursday 27 June 2024, 3.00pm-4.30pm
Sign up on PDMS

Adobe Photoshop – Introduction to Vector Graphics (in-person)
Thursday 27 June 2024, 1.00pm-5.00pm
Sign up on PDMS

PG Cafe
Thursday 27 June 2024, 2.30pm -3.30pm
Fairlie Social Area, Old Burgh School

Board Game Night
Friday 28 June 2024, 4.00pm-6.00pm
Fairlie Social Area, Old Burgh School

Microsoft PowerPoint:Essential Skills (in-person)
Tuesday 2 July 2024, 1.30pm-3.00pm
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PG Cafe
Wednesday 3 July 2024, 2.30pm -3.30pm
Fairlie Social Area, Old Burgh School

Research Synthesis and Meta-analysis in Language Education and Beyond
Wednesday 3 July 2024, 2.30pm – 4.00pm
Online – booking required

Introducing Autoethnography in Applied Linguistics: Prospects and Possibilities
Thursday 4 July 2024 , 2.30pm to 4.00pm
Online – Booking required

Independence Day Movie Night
Thursday 4 July 2024, 5.00pm – 7.00pm
Graduate School Meeting Room, Old Burgh School

Online Shut-up and Write
Friday 5 July 2024, 12.30pm-3.30pm
Email:[email protected] to signup.

Microsoft Access: Introduction to Databases (in-person)
Tuesday 9 July 2024, 9.30am – 4.00pm
Walter Bower House, Eden Campus
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Stretching and Guiding with Penny
Wednesday 10 July 2024, 5.30pm-6.30pm
Limited spaces, email:[email protected] to sign up.

Microsoft Word: Advanced Document Management
Thursday 11 July 2024, 2.00pm – 4.30pm
Town Centre Classroom
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PG Cafe
Thursday 11 July 2024, 2.30pm-3.30pm
Fairlie Social Area, Old Burgh School

Microsoft Word: Controlling Document Design (in-person)
Tuesday 16 July 2024, 2.00pm – 4.30pm
Town Centre Classroom
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Microsoft Word: Producing a Thesis (in-person)
Thursday 18 July 2024, 2.00pm – 5.00pm
Town Centre Classroom
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Microsoft Word: Manuscript and Referencing Tools
Wednesday 24 July 2024, 2.00pm-4.30pm Sign up on PDMS