MATH07026 2019 HEALTH STATISTICS AND DATA ANALYSIS
This module is designed for health science and nutrition students to provide them with, the knowledge of how to summarise and analyse data, to provide an insight into the concepts of probability and probability distributions, understanding of statistical methods for testing hypotheses, and to provide skills in using statistical software to analyse datasets.
On completion of this module the learner will/should be able to;
Describe the rationale for and methods of selecting appropriate samples for a study
Graphically display and numerically summarise data using appropriate descriptive statistics
Apply probability and probability distributions to data analysis
Choose and apply appropriate tests of hypotheses based on a research problem and the characteristics of a dataset
Model the relationships between variables using linear regression analysis
Use an appropriate statistical software package to perform statistical analysis of data
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
The student will be assessed by means of both summative and formative assessment. The summative assessment will consist of two practical based continuous assessments 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.
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 laboratory assessment or a combination of both.
The repeat practical laboratory assessment will be held in the first week of September prior to the autumn exam boards taking place.
1. Describe the rationale for and methods of selecting appropriate samples for a study
- Sample selection methods based on study design
- Sample Size
- Sampling Issues
2. Graphically display and numerically summarise data using appropriate descriptive statistics
- Graphical Representation of data including frequency tables and charts
- Measures of Central Tendency, Position and Dispersion.
- Confidence Intervals for Means and Proportion size
3. Apply probability and probability distributions to data analysis
- 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
4. Choose and apply appropriate tests of hypotheses based on a research problem and the characteristics of a dataset
- Introduction to Hypothesis Testing
- Writing hypotheses for statistical tests
- 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
5. Model the relationships between variables using linear regression analysis
- Relationship Modelling
- Pearson's Correlation Co-efficient
- Significance of the correlation co-efficient
- Spearman's Rho
6. Use an appropriate statistical software package to perform statistical analysis of data
- Introduction to SPSS
- Using SPSS to carry out the various statistical tests detailed in the syllabus above.
Coursework & Assessment Breakdown
|Title||Type||Form||Percent||Week||Learning Outcomes Assessed|
|1||Multiple Choice Self Assessment Quizzes||Formative||UNKNOWN||- %||OnGoing||1,2,3,4,5|
|2||Descriptive Statistics - Practical Assessment||Continuous Assessment||Practical Evaluation||25 %||Week 7||2,6|
|3||Inferential Statistics - Practical Assessment||Continuous Assessment||Practical Evaluation||25 %||Week 13||4,5,6|
End of Semester / Year Assessment
|Title||Type||Form||Percent||Week||Learning Outcomes Assessed|
|1||Final Exam Theory based final Exam||Final Exam||UNKNOWN||50 %||End of Term||1,2,3,4,5|
Full Time Mode Workload
|Laboratory Practical||Computer Laboratory||Statistics Practical||2||Weekly||2.00|
|Lecture||Lecture Theatre||Theory Lecture||2||Weekly||2.00|
|Independent Learning||UNKNOWN||Student Self Study||3||Weekly||3.00|
Required & Recommended Book List
2012-04-04 Statistics for the Health Sciences SAGE Publications
ISBN 9781849203364 ISBN-13 1849203369
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."
2017-08-22 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.