ADVANCED STATISTICS AND DATA ANALYSIS - 2022/3

Module Overview

The module involves a combination of 2-hour lectures and 2-hour workshops. Each week, lectures cover a specific statistical topic or concept. The theoretical and mathematical basis is explored using research examples and other types of illustrative example. Technological aids will also be incorporated to further student-centred interaction. The workshops focus on 'practising' the theoretical content of the preceding lecture. Datasets are explored and analysed using Jamovi in a student-led approach that is guided by tutors. Together, lectures and workshops provide knowledge of statistical analyses from both a theoretical and practical perspective, resulting in a broader understanding of advanced statistical methods in psychology.

Module provider

Psychology

Module Leader

PAYNE Sarah (Psychology)

Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 5

Module cap (Maximum number of students): N/A

Module Availability

Semester 1

Prerequisites / Co-requisites

PSY1020 and PSY1032: each of these modules must be completed prior to taking this module.

Module content

The weekly lectures and workshops will cover theory and practice related to and including the following indicative topic areas:
 

• Revision and introduction of statistical concepts, methods and key topics


• Advanced ANOVA-related techniques and their assumptions


• Simple and multiple regression techniques and the assumptions of regression analysis


• Logistic regression

Assessment pattern

Alternative Assessment

N/A

Assessment Strategy

The assessment strategy is designed to provide students with the opportunity to demonstrate each of the learning outcomes

Learning outcomes 1-4 are assessed by the Exam.

Thus, the summative assessment for this module consists of:

• MCQ/short answer exam (exam period), 55 questions and length of 120 minutes.

• MCQ questions in lectures

• Verbal feedback in lectures

• Tutor verbal feedback on exercises in workshops

• Feedback/answer sheet for workshops exercises

Module aims

• Correctly analyse experimental and observational data using advanced statistical procedures and understand the assumptions and limitations of these.
• Correctly interpret statistical results and understand the correct formats used to present data and results.

Learning outcomes

Methods of Teaching / Learning

The learning and teaching strategy is designed to:

Build upon material covered in modules PSY1020 and PSY1032 and develop skill in understanding multivariate statistics in preparation for the dissertation project and employment. A range of different tests are covered, but these are interlinked both in terms of interpretation and calculation. Knowledge is progressively attained with each class building upon previous classes.

The learning and teaching methods include:

• Two-hour lectures with weekly two-hour workshops.


• Lectures cover statistical theory and how to use software to run statistical analyses. Multiple choice and open-ended questions are used so that students get direct feedback on their learning.


• Workshops consist of exercises to be completed independently, in pairs, or small groups by students. Exercises involve the investigation and analysis of data sets that draw attention to specific statistical considerations or practices. Workshop tutors guide students and a written feedback sheet provides solutions to the exercises.

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list

https://readinglists.surrey.ac.uk
Upon accessing the reading list, please search for the module using the module code: PSY2017

Programmes this module appears in

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2022/3 academic year.