Introduction to Statistics - Part 1

Audience: Academic staff, PG research, Professional staff, Research staff

Date: Monday 12 October 2026 to Monday 31 May 2027

Times: null

Key details: Learn about basic statistical concepts and exploratory data analysis.

Target audience

Note that the course is not open to students on an undergraduate degree or to students on a taught postgraduate degree programme.

Qualifications needed

There are no pre-requisites for this course.

Course pre-work

There is no pre course work.

Course information

Introduction to Statistics is a self-paced, online course. The aim of this course is to introduce basic statistical concepts and analysis methods. The focus is the practical application of statistics and using R/RStudio to implement the methods.

The topics covered are divided into four sections:

I               Data collection, types, and visual and numerical summaries

II             Probability, statistical distributions, and confidence intervals

III            Hypothesis tests (t 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 language R, and user-friendly environment, RStudio.

 

It can be 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 on Moodle. Over the whole year, the time commitment is anticipated to be about 2 or 3 hours per week (working through the course notes and associated computer practical).

 

There will be an introductory session to get you started and throughout the course there will be online help sessions. The introductory help session will likely be held during week 5 and this will be confirmed closer to the time; the online help session timings are to be confirmed. You are encouraged to attend the introductory session in-person to meet the course tutor and fellow participants. Participation in the help sessions is optional. 

The course is facilitiated by the Graduate School at St Leonard's College and delivered by the Centre for Research into Ecological and Environmental Modelling. 

 

Tutors

CREEM Staff

Course provider

St Leonard's Postgraduate CollegeEmail: stlc@st-andrews.ac.uk