Module Catalogues, Xi'an Jiaotong-Liverpool University   
 
Module Code: MTH018
Module Title: Elementary Statistics
Module Level: Level 0
Module Credits: 5.00
Academic Year: 2017/18
Semester: SEM2
Originating Department: Mathematical Sciences
Pre-requisites: N/A
   
Aims
- 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

- To develop the ability to use mathematical models to simple practical problems

- To train students’ ability to learn academic content using on-line study platform

Learning outcomes 
A Understand the basic technique of descriptive statistics and be able to use different plots or graphs to make elementary data analysis;

B Grasp the basic concepts of probability, and use it to further study the discrete probability distributions (Binomial, Possion) and continuous probability distribution (Normal);

C Understand the sampling distribution and the central limit theorem and be able to use normal distribution to estimate binomial distribution;

D Understand the basic principle of confidence intervals and hypothesis testing;

E Understand the basic principle of correlation and regression;

F have a good appreciation of the link between mathematics and other subjects;
Method of teaching and learning 
Students will be expected to attend about four hours of formal lectures and tutorials in a typical week. Lectures will introduce students to the academic content and practical skills which are the subject of the module, while problem classes and tutorials will allow students to practice those skills.


In addition to contact hours, students will be expected to devote sufficient unsupervised time to private study. Private study will provide time for reflection and consideration of lecture material and background reading.


Continuous assessment including paper home assignments and quizzes will be used to test to what extent practical skills have been learnt.


Two mini projects (choose from Data analysis and visualization, linear regression and least square approach, and confidence interval and hypothesis testing) will be designed to give the students chance to apply their knowledge in the lecture to practical problems.


On-line homework (mylabplus) will be used to encourage students to perform self-study and use modern technique to finish coursework timely.


Written examinations at the end of the module constitute the major part of assessment of the academic achievement.


In order to facilitate the smooth transition to the English delivery of all modules from year 2, this module will be delivered in English.

Syllabus 
1. Introduction, data classification, principle of data collection and experimental design.

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 including intuitive meaning of probability, events, compound events, conditional probability and Bayes’ rule, and networks of unreliable components.

4. Probability Distributions

5. Discrete and continuous random variables: the probability mass function, the probability density function and distribution function. Expectation and Variance.

6. The Binomial and Poisson distributions.

7. The Normal Distribution and Approximations.

8. Confidence intervals

9. Principles of hypothesis testing

10. Correlation and regression
Delivery Hours  
Lectures Seminars Tutorials Lab/Prcaticals Fieldwork / Placement Other(Private study) Total
Hours/Semester 45     7      98  150 

Assessment

Sequence Method % of Final Mark
1 Written Exam 65.00
2 Paper Homework And Quizzes 10.00
3 Projects 10.00
4 On-Line Homework 15.00

Module Catalogue generated from SITS CUT-OFF: 8/20/2019 6:19:41 PM