Module Identifier MA12410  
Module Title BASIC DESCRIPTIVE STATISTICS AND PROBABILITY  
Academic Year 2003/2004  
Co-ordinator Dr John A Lane  
Semester Intended for use in future years  
Next year offered N/A  
Next semester offered N/A  
Pre-Requisite A or AS level Mathematics or any of MA12010, MA12510, MA12610 taken at the same time.  
Mutually Exclusive May not be taken at the same time as, or after, any of MA10020 to MA11410.  
Course delivery Lecture   22 x 1 hour lectures  
  Seminars / Tutorials   6 x 1 hour example classes  
Assessment
Assessment TypeAssessment Length/DetailsProportion
Semester Exam2 Hours  100%
Supplementary Assessment2 Hours  100%

Learning outcomes

On completion of this module, a student should be able to:

Brief description

This module starts with the descriptive statistics used for summarising and displaying data. It then introduces probability, the mathematical language of uncertainty and discusses the analysis of data in commonly occurring situations.

Aims

To introduce students to basic ways of thinking about data. To give students the methodology for summarising and interpreting data. To introduce the basic ideas of probability, random variable, probability distributions, expectation and variance.

Content

1. SUMMARISING DATA: Categories of data, frequency tables, descriptive statistics, histograms, stem and leaf plots, comparing data sets.
2. PROBABILITY: Axioms of probability, deduction in symmetric situations, classical sample space.
3. COMBINATORICS: Basic formulae with applications.
4. THE ALGEBRA OF SETS: Basic formulae with applications.
5. CONDITIONAL PROBABILITY: Definition, the chain rule, Bayes rule, applications.
6. PROBABILITY DISTRIBUTIONS: Discrete and continuous cases, the probability mass function, the density function, calculation of probabilities, distribution functions, standard distributions, use in modelling. Calculation of probabilities using Statistical Tables.
7. EXPECTATION: Definitions of expectation, variance and standard deviation; properties, calculation in specific cases.
8. THE CENTRAL LIMIT THEOREM: Statement, significance, applications, approximation of the Binomial distribution by the Normal distribution.
[Note: concepts and methodology are illustrated throughout by means of a wide variety of specific examples.]

Reading Lists

Books
** Should Be Purchased
J Murdoch & J A Barnes (1998) Statistical tables 4th. Macmillan 0333558596
M R Spiegel (1975) Schaum's Outline of Theory and Problems of Probability & Statistics. McGraw-Hill 0070602204
** Recommended Text
N A Weiss (1993) Elementary Statistics 2nd. Addison-Wesley 0201566400
** Supplementary Text
P T Strait (1989) A first course in Probability & Statistics with applications 2nd. Harcourt Brace Jovanovich 0155275232
P G Hoel (1976) Elementary Statistics 4th. John Wiley 0471403024

Notes

This module is at CQFW Level 4