City University of Hong Kong. Course Syllabus. offered by Department of Biomedical Sciences with effect from Semester A 2018 / 2019
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1 City University of Hong Kong offered by Department of Biomedical Sciences with effect from Semester A 2018 / 2019 Part I Course Overview Course Title: Course Code: Course Duration: Credit Units: Level: Proposed Area: (for GE courses only) Medium of Instruction: Medium of Assessment: Prerequisites: Precursors: Equivalent Courses: Exclusive Courses: Introductory Biostatistics and Data Analysis BMS semester 3 CUs B2 Arts and Humanities Study of Societies, Social and Business Organisations Science and Technology English English BMS1901 Calculus For Life Sciences, or MA1200 Calculus and Basic Linear Algebra 1 & MA1201 Calculus and Basic Linear Algebra II, or MA1300 Enhanced Calculus and Linear Algebra 1 & MA1301 Enhanced Calculus and Linear Algebra II 1
2 Part II Course Details 1. Abstract (A 150-word description about the course) This course aims to introduce concepts and methods of statistical analysis particularly those occurring in biomedical or biological sciences. The objective is to solve some practical issues in biomedical or biological sciences using statistical methods. Topics include descriptive measures, tests of hypotheses, significance tests, confidence levels, correlation, regression, chi-square tests and analysis of variance. 2. Course Intended Learning Outcomes (CILOs) (CILOs state what the student is expected to be able to do at the end of the course according to a given standard of performance.) No. CILOs # Weighting* (if applicable) Discovery-enriched curriculum related learning outcomes (please tick where appropriate) A1 A2 A3 1. Introduce statistics and its utility in biological and biomedical scientific context Develop analytical skills involving distributions and measures of central tendency and spread Understand the concepts of estimation and confidence 20 intervals and how they are used in statistical inference 4. Perform hypotheses tests and to interpret results for data 30 sets 5. Apply statistical methods to a range of problems 20 * If weighting is assigned to CILOs, they should add up to 100%. 100% # Please specify the alignment of CILOs to the Gateway Education Programme Intended Learning outcomes (PILOs) in Section A of Annex. A1: Attitude Develop an attitude of discovery/innovation/creativity, as demonstrated by students possessing a strong sense of curiosity, asking questions actively, challenging assumptions or engaging in inquiry together with teachers. A2: Ability Develop the ability/skill needed to discover/innovate/create, as demonstrated by students possessing critical thinking skills to assess ideas, acquiring research skills, synthesizing knowledge across disciplines or applying academic knowledge to self-life problems. A3: Accomplishments Demonstrate accomplishment of discovery/innovation/creativity through producing /constructing creative works/new artefacts, effective solutions to real-life problems or new processes. 3. Teaching and Learning Activities (TLAs) (TLAs designed to facilitate students achievement of the CILOs.) TLA Brief Description CILO No. Hours/week (if applicable) Lectures Learning through teaching is per primarily based on lectures week Lab Sessions Learning through lab sessions is primarily based on hands-on statistical problem solving allowing interaction 3 hours 3 hours Learning through take-home After class 2
3 assignments to understand basic concepts, statistical methods and some related applications in biomedical and biological sciences. 4. Assessment Tasks/Activities (ATs) (ATs are designed to assess how well the students achieve the CILOs.) Laboratory and take-home assignments 20% Project 30% Examination 50% Assessment Tasks/Activities CILO No. Weighting* Remarks Continuous Assessment: 50 % Hand-in assignments 20% The assignments will include both writing and computational exercises designed to help students develop skills in data analysis and better understand the statistical concepts presented in the lectures. Project 30% Each student will develop their own individual research question and answer it using simulated or publicly available data. Examination: _50 % (duration: 2-3 hours, if applicable) 50% The exam will cover materials presented in lectures, labs, readings and assignments. * The weightings should add up to 100%. 100% 3
4 5. Assessment Rubrics (Grading of student achievements is based on student performance in assessment tasks/activities with the following rubrics.) Assessment Task Criterion Excellent (A+, A, A-) 1. Hand-in assignments Ability to explain basic concepts of biostatistics and perform statistical computations 2. Project Ability to apply biostatistics concepts and methods to real data 3. Examination Ability to apply statistical concepts and methods to a range of problems in biological and biomedical sciences Good (B+, B, B-) Fair (C+, C, C-) Marginal (D) Failure (F) 4
5 Part III Other Information (more details can be provided separately in the teaching plan) 1. Keyword Syllabus (An indication of the key topics of the course.) Distributions, descriptive statistics, confidence intervals, hypothesis testing 2. Reading List 2.1 Compulsory Readings (Compulsory readings can include books, book chapters, or journal/magazine articles. There are also collections of e-books, e-journals available from the CityU Library.) 1. Pagano M. and Gauvreau K. Principles of Biostatistics. Pacific Grove, CA: Duxbury. 2.2 Additional Readings (Additional references for students to learn to expand their knowledge about the subject.) 1. Thomas W. MacFarland. Introduction to Data analysis and Graphical Presentation in Biostatistics with R: Statistics in the Large. 2. Bernard Rosner. Fundamentals of Biostatistics 5
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