MATH06110 2020 Applied Health Statistics

General Details

Full Title
Applied Health Statistics
Transcript Title
Applied Health Statistics
Code
MATH06110
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 SG_SPRAC_E06 202000 Certificate in Practices in Health Informatics
Description

This course introduces the student to  statistical techniques for analysing health related data. It provides the student with the ability to apply appropriate statistical techniques to data sets gathered during project work and also to comment on and rate techniques used in existing studies. The student will also be introduced to statistical techniques used to aid in the assessment of the health of a population. 

Learning Outcomes

On completion of this module the learner will/should be able to;

1.

Describe the rationale for and methods of selecting appropriate samples for a study in a health related area

2.

Use epidemiological data to evaluate the health status of a population

3.

Choose and apply appropriate tests of hypotheses based on a research problem and the characteristics of a dataset.

4.

Model the relationships between variables using appropriate statistical methods

5.

Use an appropriate statistical software package to perform statistical analysis of data

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 a practical based continuous assessment, a data analysis project 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.  

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 the student may be asked to re-sit the moodle quizzes, retake the practical evaluation assessment or resubmit the data analysis project. 

Indicative Syllabus

Describe the rationale for and methods of selecting appropriate samples for a study

  • Sampling Methods
  • Sample Size Calculations

Use epidemiological data to evaluate the health status of a population

  • Birth Rates/Death Rates/Measures of Fertility
  • Incidence/Prevalence
  • Odds Ratio
  • Relative Risk

Choose and apply appropriate tests of hypotheses based on a research problem and the characteristics of a dataset.

  • Hypothesis Testing
  • Application of One Sample, Independent Samples and Paired Samples t-tests
  • One-Way ANOVA and related Post Hoc Tests
  • Repeated Measures ANOVA and related Post Hoc Tests
  • z-tests for proportion size
  • Non Parametric Tests
    • Introduction to Non-Parametric hypothesis tests
    • Chi-Square test for association and Independence
    • Mann-Whitney test
    • Kruskal Wallis test
    • Wilcoxon signed-rank test

Model the relationships between variables using appropriate statistical methods

  • Relationship Modelling
  • Pearson's Correlation Co-efficient
  • Significance of the correlation co-efficient
  • Spearman's Rho

Use an appropriate statistical software package to perform statistical analysis of data

  • Use of SPSS to carry out the various statistical tests detailed in the syllabus above.

Coursework & Assessment Breakdown

Coursework & Continuous Assessment
100 %

Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Moodle Quizzes Continuous Assessment Open Book Exam 25 % OnGoing 1,2,3,4
2 Practical Assessment Continuous Assessment Practical Evaluation 35 % Week 8 2,3,4,5
3 Data Analysis Project Project Project 40 % Week 13 1,3,4,5

Online Learning Mode Workload


Type Location Description Hours Frequency Avg Workload
Online Lecture Distance Learning Suite Online Lecture 1 Weekly 1.00
Workshop Distance Learning Suite Online Computer based Statistics workshop 2 Weekly 2.00
Independent Learning Offsite Student Self Study 4 Weekly 4.00
Total Online Learning Average Weekly Learner Contact Time 3.00 Hours

Required & Recommended Book List

Recommended Reading
2012-04-04 Statistics for the Health Sciences SAGE Publications
ISBN 9781849203364 ISBN-13 1849203369

This is a highly accessible textbook on understanding statistics for the health sciences, both conceptually and via SPSS. The authors give clear explanations of the concepts underlying statistical analyzes and descriptions of how these analyzes are applied in health sciences research without complex statistical formulae. The book takes students from the basics of research design, hypothesis testing, and descriptive statistical techniques through to more advanced inferential statistical tests that health sciences students are likely to encounter. Exercises and tips throughout the book allow students to practice using SPSS.

Recommended Reading
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."

Recommended Reading
2018-09-03 SPSS Demystified Routledge
ISBN 9781351976350 ISBN-13 1351976354

Without question, statistics is one of the most challenging courses for students in the social and behavioral sciences. Enrolling in their first statistics course, students are often apprehensive or extremely anxious toward the subject matter. And while SPSS is one of the more easy-to-use statistical software programs available, for anxious students who realize they not only have to learn statistics but also new software, the task can seem insurmountable. Keenly aware of students anxiety with statistics (and the fact that this anxiety can affect performance), Ronald D. Yockey has written SPSS Demystified: A Simple Guide and Reference, now in its third edition. Through a comprehensive, step-by-step approach, this text is consistently and specifically designed to both alleviate anxiety toward the subject matter and build a successful experience analyzing data in SPSS. Key features of the text: Step-by-step instruction and screenshots Designed to be hands-on with the user performing the analyses alongside on their computer as they read through each chapter Call-out boxes provided, highlighting important information as appropriate SPSS output explained, with written results provided using the popular, widely recognized APA format End-of-chapter exercises included, allowing for additional practice ? Features and updates to this edition include: material updated to IBM SPSS 24 (available Fall 2016), including screenshots and data sets/end-of-chapter exercises.

Module Resources