Module Catalogues, Xi'an Jiaotong-Liverpool University

Module Code: MTH002
Module Title: Multivariable Calculus and Statistics
Module Level: Level 0
Module Credits: 5.00
Semester: SEM2
Originating Department: Mathematical Sciences
Pre-requisites: MTH013ORMTH019ORMTH023ORMTH025ORMTH027ORMTH021

 Aims To give students an elementary of multivariable Calculus and statistics; To introduce the concept of modeling and various mathematical models in practical problems; To develop students' ability to work independently and to acquire the skill of problem solving;To improve students’ ability to learn academic contents using English.
 Learning outcomes A. have an initial understanding of the basic concepts which are the subject of this module;B. have a good appreciation of the link between mathematics and other subjects;C. be able to understand the mathematical models for simple practical problems.D. describe statistical data;E. use the Binomial, Poisson and Normal distributions;F. understand the basic principle of inferential statistics.G. be able to utilize the new technology such as computer programs and online resources to perform self-study.
 Method of teaching and learning The module will be typically organized as a combination of lecturers and tutorials.
 Syllabus Part 1 Multivariable calculus 1.Functions of several variables 2.The partial derivatives 3.Maxima and minima 4.Lagrange’s multipliers 5.total differential and applications 6.Double integrals Part 2 Statistics 1. Introduction and description of data 2. Examples of what ‘Statistics’ as a discipline is about, populations and samples, graphical summaries, shape, location and spread of data. 3. Elements of Probability Theory 4. Intuitive meaning of probability, events, compound events, conditional probability and Bayes’ rule, networks of unreliable components. 5. Probability Distributions 6. Discrete and continuous random variables: the probability mass function, the probability density function and distribution function. Expectation and Variance. 7. The Binomial and Poisson distributions. 8. The Normal Distribution and Approximations. 9. The principles of hypothesis testing, 10. central limit theorem, 11. Normal confidence intervals.12. Correlation and regression.
Delivery Hours
 Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total Hours/Semester 39 13 98 150

## Assessment

 Sequence Method % of Final Mark 1 Written Examination 65.00 2 Mid-Term Test 15.00 3 Course Work Quizzes And Online Homework And Projects 15.00 4 Project 5.00
 Module Catalogue generated from SITS CUT-OFF: 1/26/2020 10:20:14 PM