MY565 Half Unit
Intermediate Quantitative Analysis
This information is for the 2020/21 session.
Teacher responsible
Prof Jonathan Jackson COL8.05
Availability
This course is available on the MPhil/PhD in Health Policy and Health Economics. This course is available as an outside option to students on other programmes where regulations permit.
This course is available to all research students where regulations permit.
Pre-requisites
Participants should have studied introductory statistics or quantitative methods before, up to an introduction to descriptive statistics and basic statistical inference. Students with no previous studies in quantitative analysis should take instead Introduction to Quantitative Analysis (MY451).
Because of the overlaps between these courses, it is not possible to take both this course and either of Introduction to Quantitative Analysis (MY451) or Applied Regression Analysis (MY452) as assessed courses.
Course content
The course is intended for students with some (even if limited) previous experience of quantitative methods or statistics. Using examples from psychological research, it covers first a review of the foundations of descriptive statistics and statistical inference, in the context of the analysis of two-way contingency tables and comparisons of means between two groups. The main topic of the course is linear regression modelling and related methods, including scatterplots, correlation, simple and multiple linear regression, and analysis of variance and covariance. An introduction to binary logistic regression modelling is also included. The computer classes give hands-on training in the application of these statistical techniques.
Teaching
This course is delivered through a combination of classes and lectures in Michaelmas Term. This year, this teaching will be delivered through a combination of short online recorded films for the lectures and live classes, which will be delivered face-to-face where feasible, or online where not. Combined hours across lectures and classes will be equivalent to a minimum of 30 hours face-to-face teaching.
This course has a Reading Week in Week 6 of MT.
Formative coursework
Self-guided computer exercises implementing statistics covered in the lectures with weekly online homework on the material covered in the lectures and exercises.
Indicative reading
A course pack will be available for download online.
Additional reading: many introductory statistics books are available. But we particularly recommend Alan Agresti and Christine Franklin (2009) Statistics: The Art and Science of Learning from Data, and Alan Agresti and Barbara Finlay (2009, 4th edition) Statistical Methods for the Social Sciences.
Assessment
Continuous assessment (20%) in the MT.
Online assessment (80%).
Three-hour online assessment (80%) in the January exam period.
Continuous assessment (20%) in the MT.
Homework and participation will constitute 20% of the final overall mark.
Important information in response to COVID-19
Please note that during 2020/21 academic year some variation to teaching and learning activities may be required to respond to changes in public health advice and/or to account for the situation of students in attendance on campus and those studying online during the early part of the academic year. For assessment, this may involve changes to mode of delivery and/or the format or weighting of assessments. Changes will only be made if required and students will be notified about any changes to teaching or assessment plans at the earliest opportunity.
Key facts
Department: Methodology
Total students 2019/20: Unavailable
Average class size 2019/20: Unavailable
Value: Half Unit
Personal development skills
- Application of numeracy skills
- Specialist skills
