PUT 902: Advanced Biostatistics and Data Science
PRE-REQUISITES:Prior knowledge of basic statistics MODULE DESCRIPTION
This course teaches the concepts of biostatistics and the application of biostatistics in real world issues. Statistical methods and principles necessary for understanding and interpreting data used in environmental health and policy evaluation and formation. Topics include descriptive statistics, graphical data summary, sampling, statistical comparison of groups, correlation, and regression.
Course Content
- Probability and advanced statistical theories
- parametric and non-parametric statistics
- Poisson distribution, Regression modelling, statistical software appreciation and bioinformatics.
Data Science introduces the concept and tools needed in turning open and real-world data into solving real world problems via mastering Data communication, data investigation, data wrangling, cleaning, sampling, exploratory analysis and data Visualization skills. Students will learn the powerful statistical program in R and how to use R for effective data analysis and statistical programming. The course will also cover practical issues in statistical computing with R, especially in reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code.
MODULE AIMS
- To guide students on proper methods of design of experiments, data collection/collation
- To introduce students to statistical methods in public health research.
- To provide guidance on various scientific methods of analyzing public health statistical data.
- To introduce students to data analysis using various statistical software packages like SPSS, R, Minitab, etc
INTENDED LEARNING OUTCOMES: On successful completion of this module student should be able to:
- interpret results to suit experimental objectives.
- present research / study results and inferences therein.
- correctly perform basic descriptive statistics on public health data.
- effectively design simple survey to obtain public health data.
- analyse data using the parametric tests
- analyse data using different statistical software.
MODULE EXECUTION PLAN:
This module shall consist of 14 lectures covering 21 topics to be delivered in a classroom setting. Additional learning experiences shall be in form of group-based tutorial, and individual seminar presentation which shall weekly or on prearranged dates for the duration of the course. Each lecturer shall ensure formative assessment of students learning achievements as well as take feedback on students’ experiences with each teaching contact. Assignments (formative and summative) shall comprise individual works and small group activities. Formative assessment shall be conducted to cover the recently completed series. At the end of the module, a final summative assessment shall be undertaken by students which will cover the entire syllabus of the module.
TEACHING AND LEARNING EXPERIENCES WITH CONTACT HOURS
Activity type | A (Applicable)/ N/A (Not applicable) | Contact hours |
---|---|---|
Lectures (L) | Applicable | 23 |
Tutorials (T) | Applicable | 3 |
Seminar presentation (SP) | Applicable | 8 |
Course paper/assignment (CP/A) | Applicable | 4 |
Practical/demonstrations (PR) | Applicable | 6 |
Self-directed learning | - | - |
Group activities | - | - |
CONTENT/ACTIVITY SCHEDULE
ACTIVITY TYPE | TOPIC | CONTACT HOURS | INSTRUCTOR |
---|---|---|---|
Lecture | Review of Descriptive Statistics | 1 | - |
Lecture | Ethic and midwifery issues in contemporary practice. | 5 | Dr. Yinka Onasoga |
Lecture | Sampling Techniques / Methods | 2 | - |
Lecture | Concept of Biostatistics | 1 | - |
Lecture | Probability and Advanced Statistical Theory I: Normal and Binomial Distributions | 2 | - |
Lecture | Probability and Advanced Statistical Theory II: Poisson and Exponential Distributions | 2 | - |
Lecture | Parametric Statistics I | 2 | - |
Lecture | Parametric Statistics II | 2 | - |
Lecture | Non-Parametric Statistics | 1 | - |
Lecture | Population Growth Models | 1 | - |
Lecture | Regression Models I: Simple and Multiple Linear Regression | 2 | - |
Lecture | Regression Models II: Logistic Regression and Transformations | 2 | - |
Lecture | Simple Survival Analysis and Clinical Trials | 1 | - |
Lecture | Correlation Coefficients I: Spearman and Pearson | 2 | - |
Lecture | Correlation Coefficients II: Partial and Multiple | 2 | - |
Practical | Statistical Software Application | 3 | - |
Practical | Statistical Software Application | 3 | - |
Assignment | Exercise on Parametric tests | NA | - |
Seminar | A statistical analysis using any of the Software | 8 | - |
Assignment | Exercise on Non-Parametric tests | NA | - |
Assignment | Analyzing actual public health data using two statistical software applications. | NA | - |
MODULE ASSESSMENT
FORMATIVE
his shall be based on the discretion of course instructor and may include but not limited to activities such as class participation and hands-on application of software, seminar presentation, take-home assignment and classroom written test.
SUMMATIVE
This shall be constituted by the continuous assessment scores, oral presentation and final examination score. Students shall be notified at least a week before a continuous summative assessment while final examination shall be as scheduled in the session calendar and according to the examination time table which shall be released as at when due. Continuous summative assessment can also be derived from class participation, seminar presentation, course paper/written assignment and classroom written tests. On the other hand, the summative assessment shall variably consist of MCQs, OSCE, Essays, and Practical.
RESIT EXAMINATION
Students whose assignments and course papers are considered unsatisfactory shall undertake compensatory tasks (e.g. write an essay or do a synopsis) to make up for the defect in performance. A student who fails to obtain a mean score of 50% and./or fail to satisfy the requirement for ‘Pass’ in a module will be entitled to re-assessment in a re-sit examination three months later. However, during the three months of preparation, the student must be given opportunity for fresh continuous assessment scores. The same criteria for the main examination shall apply to the re-sit examination.
RESOURCES (Materials for further readings in addition to the taught content of a lecture)
BOOKS:
- Rosmer. Fundamentals of Biostatistics, 7th Ed.
- Steel, R.G.D. and Torrie, J.H. Principles and Procedures of Statistics: A Biomedical Approach, 2nd Ed.
- K. Visweswara Rao. Biostatistics: A Manual of Statistical Methods for Use in Health, Nutrition and Anthropology. Jaypee Brothers Medical Publishers (P) Ltd., 1996.
- Nduka, E.C. and Ogoke, U.P. Principles of Applied Statistics, Regression and Correlation Analysis.
- Nduka, E.C. Statistics Concept and Methods
JOURNALS
- Computational Statistics & Data Analysis (Publisher: Elsevier)
- The International Journal of Biostatistics (Publisher: De Gruyter)
- Journal of Biometrics & Biostatistics (Publisher: Omics International)
- International Journal of Clinical Biostatistics and Biometrics (Publisher: ClinMed International Library)
- Scientific Journal of Biometrics & Biostatistics (Publisher: ONOMY Science)
WEB-BASED RESOURCES:
PROFILE OF MODULE INSTRUCTORS
NDUKA, Ethelbert is a Professor of Statistics in the Faculty of Science, University of Port Harcourt with effect from 2005. He holds a Ph.D from the University of Ibadan (1994). He was Dean of Science (2008-2010) and Deputy Vice-Chancellor, Administration (2011-2015) of University of Port Harcourt. He is a Fellow of Nigerian Statistical Association. His current research interest is on modeling in biometric studies, outliers/missing values in regression analysis. He has successfully supervised 5 Ph.Ds. His email address is below ethelbert.nduka@uniport.edu.ng. Download CV: CV_Nduka-Ethelbert-Chinaka_ecncv1.docx Dr. (Mrs) Ogoke earned B.Sc (Ed) (Mathematics) from the University of Nigeria Nsukka, M.Sc and Ph.D degrees in Statistics from the University of Port Harcourt. Presently she is a lecturer in the Department of Mathematics and Statistics, University of Port Harcourt. She has attended many local and international workshops and conferences where she presented her work and won a number of awards. She has published widely in both local and international journals. She is a member of relevant professional bodies such as Nigerian Statistical Association, Nigerian Mathematical Society and International Biometric Society, Washington DC, USA. She has her research interest in the area of biostatistics.
PUT 903: ICT, Technical Writing & Presentation Skills
PRE-REQUISITES:ICT and Research Methods (SCI 802). Additionally, all students are expected to have completed the online course on Good Clinical Practice. A free version of this course can be found in https://shop.crotraining.co.uk/main/courses/view/Free-Good-Clinical-Practice
Prior knowledge of basic statisticsMODULE DESCRIPTION
This module will familiarize the participants with academic writing, grammar & syntax, Use suitable punctuation and grammar, employ conventions of academic style, achieve a sense of flow in written texts, critically read academic texts, summarise, paraphrase and reference correctly, engage in effective peer review and self-monitoring, replicate appropriate thesis structure, critical thinking and problem-solving skills, summarizing, paraphrasing journal critique techniques and preparation of manuscripts and dissertation reports. Preparation and presentation at conferences and scientific meetings.
Participants would be appreciating the use of Microsoft Office words (document management functions, layout, formatting, equation, reference) excel(document management, format cells, formulas, functions, charts, sparklines, , pivot tables, validation, hyperlinks, protecting and sharing worksheet/book), PowerPoint (document management, design, formatting, header/footer, working with text/pictures, creating master slide, screen views, charts, tables, animations, presentation structure), access (designing and viewing databases, tables, relationships, finding/sorting and filtering, queries), project (Microsoft project environment, outlining project – start time, working time, list of task, organising tasks, setting deadlines and constraints etc), common software for statistical analyses, presentation skills and writing journal article and dissertation reports
Participants would also be exposed to the act of preparing manuscript preparation and various statements/guidelines/checklists for reporting academic manuscripts such as: CASP (Critical Appraisal Skill Program), CONSORT (Consolidated Standards of Reporting Trials), PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis), ENTREQ (Enhancing Transparency in REporting the synthesis of Qualitative research), COREQ (Consolidated criteria for REporting Qualitative research), CARE (CAse REport guidelines), SQUIRE (Standards for Quality Improvement Reporting Excellence), STROBE (Strengthening the Reporting of Observational Studies in Epidemiology).
MODULE AIMS
Participants completing this module at the highest level of achievement should be able to:
- Approach postgraduate education with core knowledge and skills in ICT, academic writing and personal organisation
- Use ICT effective for postgraduate research
- Prepare various kinds of scientific manuscripts
- Demonstrate proficiency in presentation at conference
INTENDED LEARNING OUTCOMES: On successful completion of this module student should be able to:
COGNITIVE
- Show good knowledge on the use of ICT as an important component of research and personal development
- Understand how to write effectively and the content structure and outline for various scientific report
- Understand how to maintain academic integrity
- Evaluate and critically appraise academic materials
PSYCHOMOTOR:
- Ability to use ICT in the conduct and reportage of research
- Use effective body language such as gestures and facial expressions
- Perform data entry and mining using appropriate software
- Create persuasive arguments
- Interpret academic discoveries
AFFECTIVE
MODULE EXECUTION PLAN:
This module will use a blended approach to learning involving lectures, e-learning, self-study, demonstration and general discussion. There will be 13 lectures covering 21 topics to be delivered both online and, in a classroom, setting. The online aspect of the course shall commence 2 weeks before the classroom lectures. Students are expected to log-in and participate actively in all activities. The classroom lectures shall run for 5 days (Monday to Friday) between the hours of 9 am and 5 pm. Additional learning experiences shall be in form of group-based tutorial, and individual assignments which shall hold once a week for the entire 4-week duration of the course. Each lecturer shall ensure formative assessment of students learning achievements as well as take feedback on students’ experiences with each teaching contact. Assignments (formative and summative) shall comprise individual works and small group activities. Formative assessment shall be conducted to cover the entire module and a final summative assessment shall be undertaken by students which will cover the entire syllabus of the module.
TEACHING AND LEARNING EXPERIENCES WITH CONTACT HOURS
Activity type | A (Applicable)/ N/A (Not applicable) | Contact hours |
---|---|---|
Lectures (L) | Applicable | 20 |
Tutorials (T) | Applicable | 6 |
Seminar presentation (SP) | Applicable | 6 |
Course paper/assignment (CP/A) | Applicable | 40 |
Practical/demonstrations (PR) | Applicable | 8 |
Self-directed learning | Applicable | 40 |
Group activities | Applicable | 10 |
CONTENT/ACTIVITY SCHEDULE
ACTIVITY TYPE | TOPIC | CONTACT HOURS | INSTRUCTOR |
---|---|---|---|
Lecture | Introduction to ICT for researchers | 2 | Baridam |
Lecture & Practical | Appreciating Microsoft tools – Word, Excel, PowerPoint, Access, Project | 4 | Baridam |
Lecture & Practical | Use of reference management software (EndNote) | 6 | Baridam |
Lecture & Practical | Statistical software for research (IBM SPSS) | 4 | Baridam |
Practical | Use of software for data management – Access, MS-SQL or MongoDB | 4 | Baridam |
Lecture | Conventions and academic writing style | 1 | Ogaji |
Lecture | Summarizing, paraphrasing and referencing | 1 | Ogaji |
Lecture | Manuscript reporting styles | 1 | Ogaji |
Lecture | Dissertation reporting styles | 1 | Ogaji |
Lecture | Formatting reports | 1 | Ogaji |
Lecture | Preparing postal and presentation slides | 1 | Ogaji |
Lecture | Making effective presentations | 1 | Ogaji |
MODULE ASSESSMENT
FORMATIVE
This shall be based on performance of the student in class participation, seminar presentation, discussion and home assignments. This is essentially for monitoring teaching and learning progress, feedback, and remediation.
SUMMATIVE
This shall be constituted by the final written examination which shall include multiple choice questions, essay-style questions and computer-based practical examination. The combination of these would constitute the final examination score. The date for the final examination shall be as scheduled in the session calendar and according to the examination time table which shall be released as at when due.
RESIT EXAMINATION
A student who fails to obtain a mean score of 50% and./or fail to satisfy the requirement for ‘Pass’ in this module will be entitled to re-assessment in a re-sit examination with three months later. However, during the three months of preparation, the student must be given opportunity for fresh continuous assessment scores. The same criteria for the main examination shall apply to the re-sit examination.
RESOURCES (Materials for further readings in addition to the taught content of a lecture)
BOOKS:
- Swales JM, Feak CB. Academic writing for graduate students: Essential tasks and skills. Ann Arbor, MI: University of Michigan Press; 2004
- Systematic reviews: CRD’s guidance for undertaking reviews in health care by the Centre for Reviews and Dissemination
- SPSS Survival Manual by Julie Pallant
JOURNALS
- Swales JM, Feak CB. Academic writing for graduate students: Essential tasks and skills. Ann Arbor, MI: University of Michigan Press; 2004.
- TLea MR, Street BV. Student writing in higher education: An academic literacies approach. Studies in higher education. 1998 Jan 1;23(2):157-72.
- Journal of Biometrics & Biostatistics (Publisher: Omics International)
- DeBehnke DJ, Kline JA, Shih RD. Research fundamentals: choosing an appropriate journal, manuscript preparation, and interactions with editors. Academic Emergency Medicine. 2001 Aug;8(8):844-50.
WEB-BASED RESOURCES:
PROFILE OF MODULE INSTRUCTORS
NDUKA, Ethelbert is a Professor of Statistics in the Faculty of Science, University of Port Harcourt with effect from 2005. He holds a Ph.D from the University of Ibadan (1994). He was Dean of Science (2008-2010) and Deputy Vice-Chancellor, Administration (2011-2015) of University of Port Harcourt. He is a Fellow of Nigerian Statistical Association. His current research interest is on modeling in biometric studies, outliers/missing values in regression analysis. He has successfully supervised 5 Ph.Ds. His email address is below ethelbert.nduka@uniport.edu.ng. Download CV: CV_Nduka-Ethelbert-Chinaka_ecncv1.docx Dr. (Mrs) Ogoke earned B.Sc (Ed) (Mathematics) from the University of Nigeria Nsukka, M.Sc and Ph.D degrees in Statistics from the University of Port Harcourt. Presently she is a lecturer in the Department of Mathematics and Statistics, University of Port Harcourt. She has attended many local and international workshops and conferences where she presented her work and won a number of awards. She has published widely in both local and international journals. She is a member of relevant professional bodies such as Nigerian Statistical Association, Nigerian Mathematical Society and International Biometric Society, Washington DC, USA. She has her research interest in the area of biostatistics.