# INTRODUCTION TO STATISTICS FOR EVIDENCE-BASED PRACTICE - 2024/5

Module code: HCRM054

## Module Overview

This is a course for health and social care professionals who want to strengthen their statistical skills and their ability to critically appraise quantitative evidence. The purpose of this module is to provide students with the key concepts and principles of statistics, and quantitative design, as applied to healthcare and social research. The module will guide students through how to develop research questions, the design principles of both observational and experimental methods, as well as the key principles and approaches to of variety of statistical techniques commonly used in health and social research and quality improvement practice.

Students will take a series of lectures and laboratory sessions to develop digital capabilities and employability skills such as choosing and implementing statistical methods on modern statistical software and reporting of statistical techniques and analysis results. Students will learn and practice handling real health data, and design, implement, and report their own statistical analyses as parts of the in-class workshops and module assessments.

### Module provider

School of Health Sciences

HARRIS Jenny (Health Sci.)

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

Independent Learning Hours: 64

Lecture Hours: 24

Seminar Hours: 24

Tutorial Hours: 2

Guided Learning: 16

Captured Content: 20

Semester 1

None

## Module content

The module will cover the following topics:

Types of study and variables

Statistical hypotheses and parametric and non-parametric tests

Multivariable analysis and regression modelling

Longitudinal data modelling and time series analysis

Survival analysis

## Assessment pattern

Assessment type Unit of assessment Weighting
Oral exam or presentation Workshop presentation 30
Coursework Research proposal and Statistical analysis plan 70

N/A

## Assessment Strategy

The assessment strategy is designed to allow students to demonstrate their acquired knowledge and skills to properly choose, implement, report, and critically appraise statistical techniques as applied to healthcare and social research and practice. Through both the formative and summative assessment, students will demonstrate their understanding and exploration of key concepts, principles and applications of statistical techniques in healthcare and social research and practice.

Thus, the summative assessment for this module consists of:

Workshop presentation and participation in questions and discussions critically appraising their own proposed research and statistical analysis plan, 10 minutes of presentation followed by 5 minutes of questions and discussions. (Addressing learning outcome 4-5) (30%)

Assessment will be based on a 3000-word written assignment comprised of detailed research proposal and statistical analysis plan to answer a quantitative research question. Students will be required to choose and detail how they would implement appropriate statistical method(s) to achieve the aim(s)/goal(s), properly report their chosen method(s) and analysis results, and critically appraise the limitation of their method(s) and analytical work. (Addressing learning outcomes 1-5) (70%)

Formative assessment Students will submit an outline of their planned presentation for workshop; feedback and guidance will be provided to ensure students are on the right track.

Feedback Students will receive written feedback from the module lead and/or teaching assistant on each of the assessment elements; this includes the weekly coursework, workshop presentation slides, and the writing and statistical programming assessments. Verbal feedback will also be provided following the workshop presentation.

## Module aims

• Introduce students to the key concepts and principles of statistics and quantitative methodology as applied to healthcare research.
• Introduce the variety of statistical techniques commonly used in health and social research and practice.
• Provide students with skills in handling real health data, including the design, critical appraisal, and implementation of statistical analyses and properly reporting analysis results.
• Equip students with knowledge and skills in R coding that will support further learning beyond the module (e.g. Machine Learning and AI).

## Learning outcomes

 Attributes Developed 001 Appraise a range of common quantitative study designs that are used in health and biomedical research and practice. K 002 Demonstrate critical understanding of and be able to distinguish between different types of variables. KC 003 Understand and apply the key concepts and principles of statistical covered in the module. KC 004 Critically evaluate, and appropriately select and implement statistical techniques for real health data. KCPT 005 Properly report and share statistical analysis results. PT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

## Methods of Teaching / Learning

The learning and teaching strategy is designed to:

• Equip the students with knowledge and to develop an enquiring mind in relation to theories of pain mechanisms and consideration of holistic factors.

• Enable students to develop a holistic approach to pain assessment and management as applied within their specific area of practice.

• Empower the students to have confidence that they can influence practice.

The learning and teaching methods include:

Lectures and discussion

Simulated learning opportunities in pain assessment.

Case study and presentations.

Seminar work

Hybrid online learning; synchronous and asynchronous.

Independent study

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.