Basic Quantitative Analysis Using R (BQA-4)
Building upon the univariate techniques introduced in the Foundations in Applied Statistics (FiAS) module, these sessions aim to provide students with a thorough understanding of statistical methods designed to test associations between two variables (bivariate statistics). Students will learn about the assumptions underlying each test, and will receive practical instruction on how to generate and interpret bivariate results using R. It introduces students to four of the most commonly used statistical tests in the social sciences: correlation, chi-square tests, t-tests, and analysis of variance (ANOVA).
The module is divided between pre-recorded mini-lectures, in which you’ll learn the relevant theory, and in-person, hands-on practical sessions, in which you will learn how to apply these techniques to analyse real data using the statistical package, R.
You will learn the following techniques:
- Cross-tabulations
- Scatterplots
- Covariance and correlation
- Nonparametric methods
- Two-sample t-tests
- ANOVA
As well as viewing the pre-recorded mini lectures via Moodle and attending the live lab sessions, students are expected to do a few hours of independent study each week.
- Postgraduate students and staff
- Further details regarding eligibility criteria are available here
Students wishing to take this modules should have:
either successfully completed Foundations in Applied Statistics, including the end-of-module test or have had previous training in introductory level statistics (verified by the Skill Check)
Students will also need a basic knowledge of R. If you have not taken FiAS using R, and have not learned R elsewhere, there are three options:
Attend the CaRM module, Introduction to R; Download the materials from “90-minute R” and work through them yourself; Email the CaRM Administrator to ask whether a space is available for the first of the FiAS lab sessions, where R is introduced.
It is not possible to ‘catch-up’ on R basics during the lab sessions and students who have an insufficient background in R will have to complete either of the above options in order to start the BQA course.
Number of sessions: 4
# | Date | Time | Venue | Trainer | |
---|---|---|---|---|---|
1 | Thu 14 Nov 10:00 - 12:30 | 10:00 - 12:30 | CaRM pre-recorded lecture(s) on Moodle | Dr Ashton Brown | |
2 | Thu 14 Nov 16:00 - 18:00 | 16:00 - 18:00 | University Centre, Hicks Room | map | Dr Ashton Brown |
3 | Thu 21 Nov 10:00 - 12:30 | 10:00 - 12:30 | CaRM pre-recorded lecture(s) on Moodle | Dr Ashton Brown | |
4 | Thu 21 Nov 16:00 - 18:00 | 16:00 - 18:00 | University Centre, Hicks Room | map | Dr Ashton Brown |
This module is very popular, so we repeat it several times. Each module runs over two sessions, covers exactly the same material, and is at the same level.
The module uses the statistical package R and the interface R-Studio; these are free to download. Instructions will be provided.
An end-of-module assessment (open-book online test). Weekly online quizzes are available to help you prepare.
There is no set text for this module; although recommended readings and all necessary information on the module's Moodle page.
Please complete the Basic Statistics Stream booking request form on the CaRM website
Please note that Basic Statistics Stream modules are repeated throughout the year and that multiple iterations are available in the Michaelmas and Lent terms.
The modules will be taught in either Stata or R. If you have a preference please indicate this in your booking request and we will try to accommodate this when making your booking. We require students to stick with the same statistical software as they progress through the Basic Statistics Stream modules so please ensure any future bookings you make align with the software you have started the sequence on.
Moodle is the 'Virtual Learning Environment' (VLE) that CaRM uses to deliver online courses.
CaRM instructors use Moodle to make teaching resources available before, during, and/or after classes, and to make announcements and answer questions.
For this reason, it is vital that all students enrol onto and explore their course Moodle pages once booking their CaRM modules via the UTBS, and that they do so before their module begins. Moodle pages for modules should go live around a week before the module commences, but some may be made visible to students, earlier.
For more information, and links to specific Moodle module pages, please visit our website
8 hours over 2 weeks (4 hours lectures; 4 hours lab)
1 morning lecture and 1 afternoon lab session per week, for 2 weeks
- Foundations in Applied Statistics Using R (FiAS-6)
- Basic Quantitative Analysis Using Stata (BQA-5)
- Doing Multivariate Analysis Using Stata (DMA-5)
- Further Topics in Multivariate Analysis Using R (FTMA-4)
Booking / availability