MATH06109 2020 Introduction to Statistics in Health Science
Full Title
Introduction to Statistics in Health Science
Transcript Title
Introduction to Statistics in
Code
MATH06109
Attendance
N/A %
Subject Area
MATH - Mathematics
Department
HEAL - Health & Nutritional Sciences
Level
06 - NFQ Level 6
Credit
05 - 05 Credits
Duration
Semester
Fee
€
Start Term
2020 - Full Academic Year 2020-21
End Term
9999 - The End of Time
Author(s)
Padraig McGourty
Programme Membership
SG_SINFO_B07 202000 Bachelor of Science in Health and Medical Information Science
SG_SINFO_C06 202000 Higher Certificate in Science in Health and Medical Information Science
Description
This modules is designed to give the students an introduction to the field of statistical analysis. The students will be introduces to the terminology required to describe the findings of statistical analysis. The module will provide the student with the ability to correctly summarise a dataset both numerically and graphically. It will provide them with knowledge of probability and probability distributions and show how these can be used to solve practical data analysis problems in the health area. The student will also get an introduction to using a software package to carry out basic descriptive analysis of a data set.
Learning Outcomes
On completion of this module the learner will/should be able to;
1.
Use appropriate terminology to describe the findings of statistical analysis
2.
Identify the correct methods for numerically summarising a dataset
3.
Use appropriate techniques to graphically summarise a dataset
4.
Apply probability and probability distributions to solve practical data analysis problems
5.
Use an appropriate statistical analysis software package to carry out descriptive analysis of a data set.
Teaching and Learning Strategies
This module will be delivered using a combination of theory based online lectures, online computer based workshops and self-study. The student's learning will be supported by a range of supplemental content available on the module page in the institutes' VLE (Moodle). This supplemental content will include notes, practical manuals and videos.
The principles of UDL will underpin the design of all module content to ensure maximum accessibility for all learners.
Module Assessment Strategies
The student will be assessed by means of both summative and formative assessment. The summative assessment will consist of two practical based assignments and a set of open book moodle quizzes where the student will be examined on both their theoretical knowledge of statistics and their use of statistical analysis software to apply this knowledge with the emphasis on the practical application of statistics. They will also take an end of module exam which will concentrate on their theoretical knowledge.
The student will also have access to online self-assessment quizzes as part of the formative assessment. These quizzes will allow the student to monitor their own progress on the module as well as identify any knowledge gaps they may have.
Repeat Assessments
Where the student fails to achieve the pass mark in the module, they may be asked to repeat the final exam or complete a practical assignment or a combination of both.
Indicative Syllabus
Use appropriate terminology to describe the findings of statistical analysis
- Basic Statistical terminology
- Symbols for parameters and statistics
- Conventions for reporting of statistics
Identify the correct methods for numerically summarising a dataset
- Measures of Central Tendency, Position and Dispersion.
Use appropriate techniques to graphically summarise a dataset
- Graphical Representation of data including frequency tables and charts
Apply probability and probability distributions to solve practical data analysis problems
- Probability Experiments
- Probability Trees
- Classical Probability
- Experimental Probability
- Addition and Multiplication Rules of Probability
- Counting Rules
- Discrete Probability Distributions
- Binomial Distribution
- Poisson Distribution
- The Normal Distribution
- Applications of the standard Normal Distribution
- Assessing Normality
- The Central Limit Theorem
Use an appropriate statistical analysis software package to carry out descriptive analysis of a data set.
- Introduction to SPSS
- Using SPSS to carry out the various statistical analysis detailed in the syllabus above
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
50 %
End of Semester / Year Formal Exam
50 %
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Moodle Quizzes - Open Book | Coursework Assessment | Assessment | 15 % | OnGoing | 1,2,3,4 |
| 2 | Graphical Summaries - Practical assignment | Coursework Assessment | Assignment | 20 % | Week 5 | 3,5 |
| 3 | Numerical Summaries - Practical Assignment | Coursework Assessment | Assignment | 15 % | Week 10 | 2,3,5 |
End of Semester / Year Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | Final Exam | Final Exam | Closed Book Exam | 50 % | End of Semester | 1,2,3,4 |
Online Learning Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Online Lecture | Distance Learning Suite | Online Lecture | 1 | Weekly | 1.00 |
| Workshop / Seminar | Distance Learning Suite | Online Computer Based Workshop | 2 | Weekly | 2.00 |
| Independent Learning | Offsite Facility | Student Self Study | 4 | Weekly | 4.00 |
Total Online Learning Average Weekly Learner Contact Time 3.00 Hours
Required & Recommended Book List
Recommended Reading
2015-04-03 Introductory Statistics for the Health Sciences Chapman and Hall/CRC
ISBN 1466565330 ISBN-13 9781466565333
2015-04-03 Introductory Statistics for the Health Sciences Chapman and Hall/CRC
ISBN 1466565330 ISBN-13 9781466565333
Introductory Statistics for the Health Sciences takes students on a journey to a wilderness where science explores the unknown, providing students with a strong, practical foundation in statistics. Using a color format throughout, the book contains engaging figures that illustrate real data sets from published research. Examples come from many areas of the health sciences, including medicine, nursing, pharmacy, dentistry, and physical therapy, but are understandable to students in any field. The book can be used in a first-semester course in a health sciences program or in a service course for undergraduate students who plan to enter a health sciences program. The book begins by explaining the research context for statistics in the health sciences, which provides students with a framework for understanding why they need statistics as well as a foundation for the remainder of the text. It emphasizes kinds of variables and their relationships throughout, giving a substantive context for descriptive statistics, graphs, probability, inferential statistics, and interval estimation. The final chapter organizes the statistical procedures in a decision tree and leads students through a process of assessing research scenarios. Web Resource The authors have partnered with William Howard Beasley, who created the illustrations in the book, to offer all of the data sets, graphs, and graphing code in an online data repository via GitHub. A dedicated website gives information about the data sets and the authors electronic flashcards for iOS and Android devices. These flashcards help students learn new terms and concepts.
Recommended Reading
2016 SPSS Survival Manual Open University Press
ISBN 033526154X ISBN-13 9780335261543
2016 SPSS Survival Manual Open University Press
ISBN 033526154X ISBN-13 9780335261543
The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software. In her bestselling guide, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report. For both beginners and experienced users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential text. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing. This sixth edition is fully revised and updated to accommodate changes to IBM SPSS procedures, screens and output. It covers new SPSS tools for generating graphs and non-parametric statistics, importing data, and calculating dates. 5 star Amazon review: "This is the book I wish I had whilst studying SPSS and experimental design on my MSc in social research methods. It is the clearest guide to SPSS that I have come across and it is very practical and easy to use. It has allowed me to revise statistical methods in a matter of days and I have gained a better understanding of these techniques than I had through using other much lengthier texts."