MATH08009 2019 APPLIED STATISTICS IN PUBLIC HEALTH

General Details

Full Title
APPLIED STATISTICS IN PUBLIC HEALTH
Transcript Title
APPLIED STATISTICS IN PUBLIC H
Code
MATH08009
Attendance
N/A %
Subject Area
MATH - Mathematics
Department
HEAL - Health & Nutritional Sciences
Level
08 - NFQ Level 8
Credit
05 - 05 Credits
Duration
Semester
Fee
Start Term
2019 - Full Academic Year 2019-20
End Term
9999 - The End of Time
Author(s)
Padraig McGourty
Programme Membership
SG_SPUBL_K08 201900 Bachelor of Science (Honours) in Public Health and Health Prom SG_SHEAL_H08 201900 Bachelor of Science (Honours) in Health Science and Physical Activity
Description

This course introduces the student to advanced statistical techniques for analysing data in the Public Health and Health Promotion fields.  It provides the students 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.

Learning Outcomes

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

1.

Demonstrate the application of advanced statistical techniques in the analysis of population health data.

2.

Describe the selection and application of appropriate quantitative analysis in global health literature and reports.

3.

Identify key features of quantitative analysis including descriptive and inferential statistics in a range of study designs.

4.

Evaluate the appropriateness of statistical approaches in a range of public health and health promotion settings.

5.

Perform statistical analysis on health data using appropriate software for statistical analysis.

Teaching and Learning Strategies

The teaching methods used will be a combination of lectures, self-study, labs, tutorials, and any combination of discussion, case study, problem-solving exercises and computer-based learning.

Module Assessment Strategies

This module will be assessed on both a theoretical and practical level.

There will be three summative assessments:

Assessment 1

This will be a classroom based assessment where the student will be assessed on their ability to use death rates and measures of morbidity and fertility to analyse the health of a population.

Assessment 2

There will be an assessment run jointly with Epidemiology on the critical appraisal of statistics used in a research study (research paper). In the part of the assessment relevant to this module, the student will be expected to identify the statistical methods used, the key results and the appropriateness of the statistical methods. 

Assessment 3

Assessment 3 will be a practical assessment using a statistical software package to carry out advanced statistical analysis on a dataset. 

The students will also be assessed formatively during class and laboratory practicals with feedback given to enable them to perform effectively in the summative assessments.

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.

Module Dependencies

Prerequisites
None
Co-requisites
None
Incompatibles
None

Indicative Syllabus

1. Demonstrate the application of advanced statistical techniques in the analysis of population health data.

  • Birth Rates/Death Rates
  • Standardisation of Death/Birth Rates (both Direct and Indirect)
  • Incidence Rates/Prevalence
  • Odds Ratio/Relative Risk/2 x 2 Tables and Chi-Square tests
  • Hazard Ratios

2.  Describe the selection and application of appropriate quantitative analysis in global health literature and reports.

  • Identification of statistical methods used in Research
  • Critical Appraisal of Statistical Methods in research

3. Identify key features of quantitative analysis including descriptive and inferential statistics in a range of study designs.

4. Evaluate the appropriateness of statistical approaches in a range of public health and health promotion settings.

5.  Perform statistical analysis on health data using appropriate software for statistical analysis.

  • Sample Size Calculations/Effect Size/Power
  • 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
  • Two Way 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
  • Relationship Modelling
  • Pearson's Correlation Co-efficient
  • Significance of the correlation co-efficient
  • Spearman's Rho
  • Simple Linear Regression/Multiple Regression analysis
  • Reliability Analysis
  • Advanced Charts for Public Health and Epidemiology (Forest Plots etc.)
  • Time to Event Analysis/Survival Analysis
  • Factor Analysis

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 Death Rate Calculations, Measures of Morbidity and Fertility Continuous Assessment Assessment 15 % Week 5 1
2 Critical Appraisal - Use of Statistics in Research Continuous Assessment Assessment 20 % Week 9 2,3,4
3 Data Analysis - Practical Assessment Continuous Assessment Practical Evaluation 15 % Week 13 5

End of Semester / Year Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 End of Module Exam Final Exam Closed Book Exam 50 % End of Term 1,2,3,4
             
             

Full Time Mode Workload


Type Location Description Hours Frequency Avg Workload
Lecture Lecture Theatre Lecture 2 Weekly 2.00
Laboratory Practical Computer Laboratory Statistics Practical 1 Weekly 1.00
Independent Learning UNKNOWN Self Study 4 Weekly 4.00
Total Full Time Average Weekly Learner Contact Time 3.00 Hours

Required & Recommended Book List

Recommended Reading
2011-08-17 Biostatistics: An Applied Introduction for the Public Health Practitioner Cengage Learning
ISBN 9781111035143 ISBN-13 1111035148

BIOSTATISTICS: AN APPLIED INTRODUCTION FOR THE PUBLIC HEALTH PRACTITIONER is designed to help public health researchers, practitioners, and students understand and apply essential biostatistics concepts. This innovative new text emphasizes real-world public health problems and the research questions they inspire. This text provides a unique introduction to statistical concepts and methods used by working professionals during investigations. Unlike other texts that assume a strong knowledge of mathematics or rely heavily on formulas, BIOSTATISTICS consistently emphasizes the public health context, making even complex material both accessible and relevant. The first chapter introduces common statistical terminology by explaining them in clear language, while subsequent chapters explore the most useful and versatile statistical methods for a variety of public health research questions. For each type of question, the author presents a range of applicable methods, from descriptions of data to simple statistical tests, generalized linear models, and multiple variable regression. The text's step-by-step coverage of fundamental concepts is perfect for students new to the field, but its depth and detail also make it ideal for two-course series in M.P.H. or M.H.A. programs, or for working professionals. Readers at all stages of their professional lives can draw on this invaluable resource to help them interpret and conduct statistical studies and support effective evidence-based practice. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Recommended Reading
2016-04-01 SPSS Survival Manual
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
2013-01-09 Biostatistics Wiley
ISBN 1118302796 ISBN-13 9781118302798

This 10th edition of Biostatistics: A Foundation for Analysis in the Health Sciences, 10th Edition should appeal to the same audience for which the first nine editions were written: advanced undergraduate students, beginning graduate students, and health professionals in need of a reference book on statistical methodology. Like its predecessors, this edition requires few mathematical prerequisites. Only reasonable proficiency in algebra is required for an understanding of the concepts and methods underlying the calculations. The emphasis continues to be on an intuitive understanding of principles rather than an understanding based on mathematical sophistication. For most of the statistical techniques covered in this edition, we discuss the capabilities of one or more software packages (MINITAB, SAS, SPSS, and NCSS) that may be used to perform the calculations needed for their application. Resulting screen displays are also shown.

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
2008-09-09 Quantitative Methods for Health Research John Wiley & Sons
ISBN 9780470022740 ISBN-13 0470022744

Quantitative Research Methods for Health Professionals: A Practical Interactive Course is a superb introduction to epidemiology, biostatistics, and research methodology for the whole health care community. Drawing examples from a wide range of health research, this practical handbook covers important contemporary health research methods such as survival analysis, Cox regression, and meta-analysis, the understanding of which go beyond introductory concepts. The book includes self-assessment exercises throughout to help students explore and reflect on their understanding and a clear distinction is made between a) knowledge and concepts that all students should ensure they understand and b) those that can be pursued by students who wish to do so. The authors incorporate a program of practical exercises in SPSS using a prepared data set that helps to consolidate the theory and develop skills and confidence in data handling, analysis and interpretation.

Module Resources

Non ISBN Literary Resources

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Journal Resources

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URL Resources
Other Resources

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Additional Information

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