Module Catalogue 2024/25

Pre Requisite Comment

N/A

Co Requisite Comment

N/A

Aims

This module aims to provide an introduction to research methods and statistical analysis.

The module is taken by both BSc and IM students. The BSc students will combine this course with the Research Methods in Practice module in Year 2, enabling students to understand the application of research methods to the clinical contexts in which they will be working using evidence-based principles. The IM students will combine years 1 and 2 with more advanced study leading to the dissertation in years 3 and 4. Throughout the course, learning is cumulative, one year building on another, with concepts recurring and developing over the course.

The main objective of this course is to help you understand the principles of experimental design and provide you with an introduction to statistics. We hope that after you complete this course you will be able to understand how a diverse range of research methods are employed to collect data, to analyse data systematically, to describe data faithfully, to formulate hypotheses and use data to evaluate those hypotheses.

The concepts, knowledge and skills this module introduces are also fundamental to just about every other module you will follow: you will need material from this module for your child study, for all your clinical placement case studies and case presentations throughout your programme. You will need to have learned all the material to make sense of the psychology modules, child development modules, and speech language pathology modules. Every article you read, test you evaluate, treatment you plan, diagnosis you propose, prognosis you make, essay you write will require recourse to concepts, facts and techniques which you will start to learn about in this module.

The module will be delivered as a mixture of lectures, lab sessions and participation in research studies.

For students studying the clinical programmes (BSc Speech & Language Therapy and Masters of Speech & Language Sciences), the HCPC Standards of Proficiency are of relevance.
13.9 recognise the value of research to the critical evaluation of practice
13.8 recognise a range of research methodologies relevant to their role
13.10 critically evaluate research and other evidence to inform their own practice

Outline Of Syllabus

Syllabus

Semester 1 lectures
Introduction to the course. Different sorts of enquiry and research methods. Evidence based practice as a framework, Population vs. samples. Descriptive vs. inferential statistics. Measures of central tendency: mean, median, mode.
Measures of dispersion: ranges, mean deviation, standard deviation; standard error. Frequency distributions.
Normal distribution and its properties. Standard scores: z-scores, t scores, percentiles. Parametric vs. nonparametric statistics.
Types of data: nominal, ordinal, interval, ratio. Basic experimental designs: between subjects and within subjects. Dependent and independent variables. Hypotheses and tails.
Hypothesis testing: probability, significance, alpha levels, type I and II errors, effect size. Introduction to inferential statistics. Choosing tests and reporting tests.

Semester 1 lab practicals
Lab: Introduction to statistical software (such as SPSS). Nonparametric tests for one and two samples nominal data.
Lab: Nonparametric tests for comparing two samples of ordinal data.
Lab: Parametric and nonparametric tests for comparing one or two samples: t tests, Wilcoxon, Mann-Whitney.
Lab: Parametric and nonparametric tests for comparing three or more samples: one way analysis of variance, kruskal wallis.
Lab: Correlation measures: tests of association and relation.
Revision for the semester and preparation for class test.

Semester 1 and Semester 2 Research Participation
Completion of a total of three hours of research work as a participant, from a range of experimental research studies available (or completion of a 1500-word essay on a subject connected with research design or ethics to be agreed with the module leader).

For students studying the clinical programmes (BSc Speech & Language Therapy and Masters of Speech & Language Sciences), relevant aspects of RCSLT curriculum guidelines:
This module contributes to the key graduate capabilities around research and evidence-based practice (4.2.4), with a focus on section B research skills and methods allowing the students to demonstrate the knowledge and skills required to understand, interpret and apply research to practice.

Intended Knowledge Outcomes

(a) Knowledge of the principles underlying experimental design
(b) Knowledge of experimental and observational designs exploring differences between groups and relationships between variables, including (i) conceptual foundations (ii) knowledge of when it is appropriate to use differenet designs, and (iii) potential pitfalls.
(c) knowledge of the principles underlying statistical analysis including knowledge of when it is appropriate to use different statistical analyses

Intended Skill Outcomes

(a) Ability to create an experimental design to address a specific hypothesis
(b) Ability to prepare data ready for a statistical analysis
(c) Ability to use a range of statistical techniques to analyse data (non parametric and parametric statistics using within and between group design) using appropriate statistical software (e.g. SPSS)

Teaching Rationale And Relationship

The lecture sessions (held in a lecture theatre) introduce essential theories, facts and techniques. In the practical sessions (held in a computer lab) students work with given scenario datasets, entering data into SPSS and analyzing it under close supervision combining computer/statistical skills acquired as part of the teaching of the module. In the research participation sessions, students gain practical experience of a range of techniques used to collect speech and language data, with debriefing sheets provided after each experiment to explain the particular design and techniques used, along with contact details of the principal investigator should the student have further queries.

Assessment Rationale And Relationship

The online digital Inspera exam assesses skills in identifying from a scenario the data to be used, the appropriate statistical test to use to answer a given scenario/question and carrying out the analyses using statistical software.

The research participation sessions have no assessment marks associated with them: the students are just required to sample a range of research methods through practical participation, over semester 1 and 2.

General Notes

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