MATH09006 2019 Statistical Analysis for Nutritional Research
Full Title
Statistical Analysis for Nutritional Research
Transcript Title
Statistical Analysis for Nutri
Code
MATH09006
Attendance
N/A %
Subject Area
MATH - Mathematics
Department
HEAL - Health & Nutritional Sciences
Level
09 - NFQ Level 9
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_SSPOR_O09 201900 Postgraduate Diploma in Science in Sports and Exercise Nutrition
SG_SSPOR_M09 201900 Master of Science in Sports and Exercise Nutrition
SG_SSPOR_O09 202400 Postgraduate Diploma in Science in Sports and Exercise Nutrition
SG_SSPOR_M09 202400 Master of Science in Sports and Exercise Nutrition
Description
This module will equip the student with advanced statistical techniques for analysing data in the Nutrition 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.
Formulate conclusions by applying a range of advanced statistical techniques in the analysis of data sets.
2.
Model the relationships between variables using regression analysis
3.
Explain the concept of survival analysis and apply the most commonly used mortality/survival functions
4.
Justify the selection and application of appropriate quantitative analysis in nutrition related literature and reports.
5.
Use a statistical software package to carry out analysis on data sets.
Teaching and Learning Strategies
The teaching methods used will be a combination of online lectures, self study, on line tutorials, problem solving exercises and computer based learning
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 projects where the student will be examined on both their theoretical knowledge of data analysis and 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 to complete an online end of module exam which will be in the form of an open book quiz.
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
The student will be given a opportunity to do a repeat practical project covering the learning outcomes assessed in the projects detailed in the assessment strategy if they do not meet the requirements to pass the module and their project work was of a sub standard level.
Indicative Syllabus
Formulate conclusions by applying a range of advanced statistical techniques in the analysis of data sets.
- Introduction to Biostatistics
- Incidence Rates/Prevalence
- Odds Ratio/Relative Risk/2 x 2 Tables and Chi-Square test
- 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
- Mann-Whitney test
- Kruskal Wallis test
- Wilcoxon signed-rank test
- Reliability Analysis
- Factor Analysis
Model the relationships between variables using regression analysis
- Pearson's Correlation/Spearman's Correlation
- Simple Linear Regression
- Multiple Linear Regression
- Logistic Regression
- Stepwise Regression
Explain the concept of survival analysis and apply the most commonly used mortality/survival functions
- Hazard Functions
- Survival Functions
- Censoring
- Kaplan-Meier
- Hazard Ratio
- Log Rank Test
- Cox Proportional Hazards Model
Justify the selection and application of appropriate quantitative analysis in public health and nutrition related literature and reports.
- Identification of statistical methods used in Research
- Critical Appraisal of Statistical Methods in research
Use a statistical software package to carry out analysis on data sets.
- The Latest version of IBM SPSS Statistics will be used to perform a number of the statistical procedures detailed earlier in the Syllabus.
Coursework & Assessment Breakdown
Coursework & Continuous Assessment
100 %
Coursework Assessment
| Title | Type | Form | Percent | Week | Learning Outcomes Assessed | |
|---|---|---|---|---|---|---|
| 1 | End of Module Online Test | Coursework Assessment | Open Book Exam | 30 % | Week 13 | 1,2,3,4 |
| 2 | Application of Statistical Methods Project | Coursework Assessment | Assignment | 35 % | Week 6 | 1,2,5 |
| 3 | Application of Statistical Methods Project 2 | Coursework Assessment | Assignment | 35 % | End of Term | 3,4,5 |
Online Learning Mode Workload
| Type | Location | Description | Hours | Frequency | Avg Workload |
|---|---|---|---|---|---|
| Lecture | Distance Learning Suite | Online Lecture | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Weekly Practical Activities | 2 | Weekly | 2.00 |
| Independent Learning | Not Specified | Self Study | 2 | Weekly | 2.00 |
Total Online Learning Average Weekly Learner Contact Time 2.00 Hours
Required & Recommended Book List
Recommended Reading
2018-11-13 Biostatistics Wiley
ISBN 9781119282372 ISBN-13 1119282373
2018-11-13 Biostatistics Wiley
ISBN 9781119282372 ISBN-13 1119282373
The ability to analyze and interpret enormous amounts of data has become a prerequisite for success in allied healthcare and the health sciences. Now in its 11th edition, Biostatistics: A Foundation for Analysis in the Health Sciences continues to offer in-depth guidance toward biostatistical concepts, techniques, and practical applications in the modern healthcare setting. Comprehensive in scope yet detailed in coverage, this text helps students understandand appropriately useprobability distributions, sampling distributions, estimation, hypothesis testing, variance analysis, regression, correlation analysis, and other statistical tools fundamental to the science and practice of medicine. Clearly-defined pedagogical tools help students stay up-to-date on new material, and an emphasis on statistical software allows faster, more accurate calculation while putting the focus on the underlying concepts rather than the math. Students develop highly relevant skills in inferential and differential statistical techniques, equipping them with the ability to organize, summarize, and interpret large bodies of data. Suitable for both graduate and advanced undergraduate coursework, this text retains the rigor required for use as a professional reference.
Recommended Reading
2017-02-17 Essentials of Biostatistics in Public Health Jones & Bartlett Learning
ISBN 9781284108194 ISBN-13 1284108198
2017-02-17 Essentials of Biostatistics in Public Health Jones & Bartlett Learning
ISBN 9781284108194 ISBN-13 1284108198
Study designs -- Quantifying the extent of disease -- Summarizing data collected in the sample -- The role of probability -- Confidence interval estimates -- Hypothesis testing procedures -- Power and sample size determination -- Multivariable methods -- Nonparametric tests -- Survival analysis -- Data visualization
Recommended Reading
2012 Statistics for Sport and Exercise Studies Routledge
ISBN 9780415595575 ISBN-13 0415595576
2012 Statistics for Sport and Exercise Studies Routledge
ISBN 9780415595575 ISBN-13 0415595576
Statistics for Sport and Exercise Studies guides the student through the full research process, from selecting the most appropriate statistical procedure, to analysing data, to the presentation of results, illustrating every key step in the process with clear examples, case-studies and data taken from real sport and exercise settings. Every chapter includes a range of features designed to help the student grasp the underlying concepts and relate each statistical procedure to their own research project, including definitions of key terms, practical exercises, worked examples and clear summaries. The book also offers an in-depth and practical guide to using SPSS in sport and exercise research, the most commonly used data analysis software in sport and exercise departments. In addition, a companion website includes more than 100 downloadable data sets and work sheets for use in or out of the classroom, full solutions to exercises contained in the book, plus over 1,300 PowerPoint slides for use by tutors and lecturers. Statistics for Sport and Exercise Studies is a complete, user-friendly introduction to the use of statistical tests, techniques and procedures in sport, exercise and related subjects. Visit the companion website at: www.routledge.com/cw/odonoghue
Recommended Reading
2010 Statistics for Sports and Exercise Science Prentice Hall
ISBN 0132042541 ISBN-13 9780132042543
2010 Statistics for Sports and Exercise Science Prentice Hall
ISBN 0132042541 ISBN-13 9780132042543
Statistics in Sport and Exercise Science assumes no prior knowledge of statistics and uses real-life case studies to introduce the importance of statistics in sport and exercise science. Statistical tests and techniques are described here in a friendly and easy-to-understand manner, giving you the confidence to analyses data and complete your own statistical studies. This is the best statistics text I have come across in 7 years of teaching on undergraduate sport degrees. Students have always struggled to see the application of statistics to their degree Statistics for Sports and Exercise Science eliminates this problem, - Dr Mick Wilkinson, Department of Sport Sciences, Northumbria University "Easily the best book in the area, specific material for sport students."- Dr Rodney Kennedy, School of Sport Studies, University of Ulster "I really like the Newell book and will definitely be recommending it to the students on my two research methods modules... The information in the book is first class." - Dr Adrian W Midgley, Department of Sport, Health and Exercise Science, University of Hull Incredibly easy to read, full of real-life examples, and very much appropriate for Sports Science students. - Dr Kate Reed, Department of Biological Sciences, University of Essex
Recommended Reading
2012-09-10 Statistics in Food Science and Nutrition Springer Science & Business Media
ISBN 9781461450092 ISBN-13 1461450098
2012-09-10 Statistics in Food Science and Nutrition Springer Science & Business Media
ISBN 9781461450092 ISBN-13 1461450098
Many statistical innovations are linked to applications in food science. For example, the student t-test (a statistical method) was developed to monitor the quality of stout at the Guinness Brewery and multivariate statistical methods are applied widely in the spectroscopic analysis of foods. Nevertheless, statistical methods are most often associated with engineering, mathematics, and the medical sciences, and are rarely thought to be driven by food science. Consequently, there is a dearth of statistical methods aimed specifically at food science, forcing researchers to utilize methods intended for other disciplines. The objective of this Brief will be to highlight the most needed and relevant statistical methods in food science and thus eliminate the need to learn about these methods from other fields. All methods and their applications will be illustrated with examples from research literature.
Module Resources
Non ISBN Literary Resources
NA
Journal Resources
NA
URL Resources
Other Resources
NA
Additional Information
NA