## APPLIED STATISTICS AND DATA ANALYSIS FOR PUBLIC HEALTH

 SHE Level 5 SCQF Credit Points 15.00 ECTS Credit Points 7.50 Module Code MMB725024 Module Leader Abdul-Razak Abubakari School School of Health and Life Sciences Subject Nursing Trimesters A (September start) B (January start)

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### Summary of Content

This module aims to develop knowledge and skills in interpreting statistical information, designing statistical data analysis plan and executing appropriate statistical data analysis to address a given public health related question. At the end of the module students will be able to interpret statistical information presented in journal articles and public health reports including the interpretation of concepts such as p-values, power and confidence intervals; perform relevant descriptive statistics to summarise statistical and/or epidemiological data using relevant measures such as frequencies, means and standard deviations; appropriately present statistical and/or epidemiological information e.g. using tables, histograms and charts; determine appropriate statistical/epidemiological analyses to use for investigating relevant statistical inferences and hypotheses testing. Students will be supported to demonstrate statistical data entry skills and the ability to plan and conduct data analyses to answer relevant public health related questions using relevant statistical software.

### Syllabus

-360b7 Types of variables b7 Measures of central tendency (e.g. mean, median) b7 Basic statistical/epidemiological data entry and management b7 Normal distribution b7 Hypothesis testing b7 Frequencies, Proportions and percentages b7 Investigating differences between two or more groups b7 Investigating relationships between variables (correlations) b7 Comparing rates of health events in populations using relevant measures of associations b7 Predicting an outcome variable from one or more predictor variables (regressions) b7 Non-parametric statistical methods

### Learning Outcomes

1 Learning outcomesOn successful completion of this modulethe student should be able to:1. Demonstrate the ability to use statistical software to summarise and present epidemiological data using relevant statistical measures 2. Employ relevant graphical formats (e.g. histogram, line graph, pie chart) to appropriately present epidemiological data 3. Test normal distribution and other relevant assumptions of parametric tests before embarking on formal statistical testing4. Identify inferential statistical techniques and test statistics appropriate for use in investigating public health related questions5. Demonstrate understanding and application of p-value, confidence intervals, sample size and power and the relevance of these in the interpretation of statistical results6. Compare risk between population groups using appropriate statistical and epidemiological tests (e.g. exposed/unexposed groups in cohort studies; cases/controls in case control studies) and critically evaluate the impact of public health interventions7. Critically evaluate and predict relationships between two or more variables using appropriate statistical techniques including correlations and various regression techniques.

### Teaching / Learning Strategy

The module is delivered online via GCU Learn and classroom based. Students may elect to study the module EITHER online OR on campus, but may not transfer between both. The overarching philosophy of the module is to equip students with the requisite skills to be able to apply social determinants of health approach in critically identifying, analysing and evaluating public health related issues. Teaching and learning activities are carefully employed to suit a diverse student population and wherever appropriate teaching/learning materials are chosen to reflect local, national and/or international contexts. Main activities carried out by students are directed and independent study to develop knowledge and skills relating to the identified learning outcomes. The teaching and learning strategies employed include: lectures / video lectures, narrated presentations, lab-based practical workshops, seminars / online asynchronous group discussions and tutorials / online self-directed study to engage students in the key concepts which will then be developed through directed reading, guided activities, literature searching and student initiated reading. In relation to public health application, students are encouraged to reflect upon the types of epidemiological data and appropriate ways to interpret and present these in public health reports. Additionally, students are guided to create data files, enter statistical/epidemiological data into statistical software and conduct analysis to answer relevant public health related questions. For example, investigating differences in the levels of a public health related variable between different population groups to justify the need for action; and/or determining the effectiveness of a public health intervention using appropriate statistical methods and techniques. Students are expected to critically appraise the value of relevant field specific literature. Teaching datasets simulating UK and international datasets such as the Health Survey for England, the Scottish Health Survey and data from the WHO InfoBase will be used for practical data analysis sessions. Individual and group-based formative assessment opportunities are provided to enable students identify learning strategies to meet their personal learning needs.

BARTON, B. & PEAT J., 2014. Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal. 2 nd ed. Chichester: Wiley-Blackwell. DANCEY, C., REIDY, J. & ROWE, R., 2012. Statistics for the Health Sciences: A Non-Mathematical Introduction. London: Sage Publications. ALTMAN, D., 2000. Statistics with confidence: Confidence Intervals and Statistical Guidelines. 2 nd ed. London: BMJ books DOS-SANTOS-SILVA, I.1999. Cancer Epidemiology: Principles and Methods. Lyon, France: World Health Organisation's International Agency for Research on Cancer (IARC). FIELD, A. 2013. Discovering Statistics using IBM SPSS Statistics. London: Sage Publications. HEBEL, J.R. & MCCARTER, R.J., 2012. A study guide to Epidemiology and Biostatistics. 7 th ed. Washington: Jones and Bartlett Learning. KIRKWOOD, B.R. STERNE, J. A. C., 2003. Essential Medical Statistics. 2 nd Ed. Oxford: Wiley-Blackwell. PALLANT, J., 2016. SPSS survival manual: a step by step guide to data analysis using IBM SPSS. 6 th ed. Maidenhead: Open university press. ROTHMAN K.J., GREENLAND S. & LASH T.L., 2008. Modern Epidemiology. 3 rd ed. Philadelphia: Lippincott Williams & Wilkins. TABACHNIK, B. G. & FIDELL, L.S., 2014. Using multivariate statistics. 6 th ed. Harlow: Pearson Education Limited. WOOD M., 2014. Epidemiology: Study Design and Data Analysis. 3 rd ed. London: CRC press (Taylor & Francis group).

### Transferrable Skills

-360b7 Work in a self-directed manner, taking responsibility for own learning, personal development b7 Develop study and IT skills to underpin effective learning b7 Develop communication skills; written, oral and listening b7 Demonstrate an ability to contribute to professional discussion b7 Work effectively with others b7 Underpin professional development by integration of theory and practice b7 Develop enhanced awareness of connections between knowledge, skills and values in relation to self and others b7 Demonstrate critical thinking and problem solving skills in a range of situations

### Module Structure

Activity Total Hours
Directed Learning 12.00
Lectures 24.00
Assessment 30.00
Directed Learning 72.00
Tutorials 4.00
Workshops 8.00

### Assessment Methods

Component Duration Weighting Threshold Description
Essay n/a 100.00 50% Essay (3000 words)