Module Catalogues, Xi'an Jiaotong-Liverpool University   
 
Module Code: DPH101
Module Title: Methods for Analysing Public Health II: Biostatistics I
Module Level: Level 1
Module Credits: 5.00
Academic Year: 2019/20
Semester: SEM1
Originating Department: Health and Environmental Science
Pre-requisites: N/A
   
Aims
The aim of this module is to provide students with a basic introduction to statistical reasoning in health science. Students will gain fundamental statistical skills that are used in investigations of a range of issues relevant to the health of populations. The module will cover methods of summarizing data, the process of statistical inference and the use of estimation techniques.
Learning outcomes 
A. Discuss the importance of data in health science, including the importance of proper data collection, analysis and interpretation

B. Identify the nature of statistical inference as applied to health science

C Outline estimation and testing methods in the analysis of univariate and bivariate relationships

D Interpret the results of data analysis correctly and effectively with minimal reliance on statistical jargon.

E Describe how to use statistical software to summarize data numerically and visually to perform data analysis.

Method of teaching and learning 
The module will be taught in a blended style. That is to say, students will be expected to access and digest learning materials – lectures and readings – prior to in-class sessions. Classroom sessions will take place in a laboratory setting where the focus will be in the application of the learned material in the form of group activities and guided exercises. Each session will end with a summative assessment task.
Syllabus 
Week 1 Statistics in Health. Introduction to the use of course and the use of statistics in health.


Week 7 – MIDTERMS


Week 8 Estimation Is Better Then Than Testing Hypotheses.

The importance of estimation methods.

Week 9 Statistics at Work I: Comparing Two Means.

Techniques used in comparing two means.

Week 10 Statistics at Work II: Comparing More Than Two Means.

Techniques used in comparing three or more means.

Week 11 Statistics at Work III: Comparing Proportions.

Techniques in the analysis of proportions.

Week 12 Statistics at Work IV: Correlation

. Introduction to the concept of correlation.

Week 13 Statistics at Work V: Simple Linear Regression.

Introduction to the concept of linear regression.


Week 14 Revision– REVISION

Delivery Hours  
Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total
Hours/Semester       52    98  150 

Assessment

Sequence Method % of Final Mark
1 Weekly Quizzes 15.00
2 Weekly Submission Of Laboratory Work 15.00
3 Midterm 30.00
4 Final 40.00
901 Weekly Quizzes(The First Sit Mark Will Be Carried Forward) 15.00
902 Weekly Submission Of Laboratory Work(The First Sit Mark Will Be Carried Forward) 15.00

Module Catalogue generated from SITS CUT-OFF: 12/8/2019 2:51:33 AM