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- Acute and Hyperacute Stroke
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- Applied clinical Anatomy 1
- Applied clinical Anatomy 2
- Applied Surgical Anatomy
- Assessment and Measurement
- Assistive Technologies in Neuromuscular Rehabilitation
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- Communication Skills for Health Professionals in Clinical Practice
- Community Stroke: Prevention and Life after Stroke
- Concepts of Neurological Rehabilitation
- Contemporary Challenges in Healthcare Ethics and Law
- Contemporary Mental Health Issues in Primary Care
- Core Skills in the Care of Critically Ill Surgical Patients
- Dissertation
- Drug Therapy in Rheumatology Practice
- Dynamic Ultrasound Imaging
- End of Life Care in Non-Specialist Settings
- Essentials of Manual Therapy for Peripheral Joint Dysfunction
- Essentials of Manual Therapy for Spinal Dysfunction
- Evidence Based Practice
- Foundation Medical Practice Award
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- Holistic Support Through to End of Life
- Human Dimensions of End of Life Care
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- Introducing Acupuncture
- Introducing Acupuncture APEL
- Introduction to Clinical Effectiveness in R. Nursing
- Leadership and Management for Healthcare Professionals
- Literature Searching and Synthesis
- Managing Change and Quality Improvement
- Medical Education
- Motor Control APEL
- Motor Control Retraining of Movement Dysfunction
- Multivariate Methods
- Musculoskeletal Management at the Interface
- Peadiatric Endocrinology
- Performance Stability
- Performance Stability APEL
- Physical Assessment B Lower Limb and Spine
- Physical Assessment in Rheumatology Nursing
- Physiology and Pharmacology of Pain
- Physiology of Neuromusculoskeletal Tissues
- Practice Development and Advancement through Work Based Learning
- Primary/Secondary Care Interface
- Principles and Practice of Joint and Soft Tissue Injection
- Project - Clinical Medicine
- Psychological and Social Aspects of R. Nursing
- Psychosocial Aspects of Pain
- Public Health and Social Policy
- Quantitative Data Analysis 1
- Quantitative Data Analysis 2
- Recognising the End of Life
- Reflective Practice
- Reliability Analysis
- Research Methods
- Research Outcomes in Arthritis and Outcomes in R.N.
- Specialist Community Practice
- Statistics and Epidemiology
- Strategic Management of Patients with Long Term Conditions
- Stroke Research
- Stroke Service Development and Improvement
- The Developing Child
- Work Based Learning
- Individual Modules
- Schools and College Liaison
This module is run within the School of Sociology and Criminology but is often chosen by Health students
Module Learning Outcomes/Objectives:
The student should be able to demonstrate:
- An understanding of key concepts and principles in statistical analysis
- Judicious selection and interpretation of descriptive statistical procedures
- Judicious selection and interpretation of inferential statistical procedures
- Competence in the use of SPSS for statistical analyses
Module Code - CRI-40022
Module Dates
to be advised
Module Aims:
- To develop students’ conceptual understanding of fundamental issues in statistical theory and practice
- To enable a critical understanding of the rationale and assumptions of descriptive and inferential statistics, and the role of data visualization techniques
- To provide an understanding of the application of a range of elementary univariate and bivariate statistical analysis techniques, and a critical appreciation of their appropriateness
The course is aimed at students interested in acquiring skills in quantitative data analysis in social and health sciences.
Candidates should normally have a first or second class honours degree in a relevant professional or academic area (e.g. medicine, physiotherapy, sociology, psychology, politics).
The module CLM-40006 Statistics and epidemiology is an excluded combination.
Module Content:
Basic statistical concepts: levels of measurement, types of data, descriptive summaries; Graphical summaries and their (in)appropriate use; The logic of hypothesis testing; The meaning of conditional probability and statistical significance; Type 1 and Type 2 errors; Basics of estimation; confidence intervals; Introduction to scale construction; Statistical tests and their assumptions: chi-square, tests for differences in means and medians, correlation and bivariate regression, oneway ANOVA and a posteriori testing; Use of SPSS for statistical analysis.
Teaching Format
Four days, over a four week period. Involves classroom instruction and practical SPSS sessions.The morning usually consists of lectures and discussion and the afternoon of sessions in the computer laboratory.
Assessment Type:
30% marks - A series of data analysis/interpretation exercises and explanations of key conceptual issues
70% marks - A 3000 word data analysis report
Keele University