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 (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 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.
Timetable
| 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.
Eligibility
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].