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2007/8 Module Catalogue
 Module Code: ENG2043 Module Title: STATISTICS FOR BUSINESS
Module Provider: Engineering Teaching Group Short Name: SE5204 Previous Short Name: SE5204
Level: HE2 Module Co-ordinator: ROCKLIFF NJ Dr (Eng Teach Gp)
Number of credits: 10 Number of ECTS credits: 5
 
Module Delivery
Autumn Semester
Assessment Requirements
Units of Assessment
Method(s)
Weighting towards Module Mark (%)
Examination
2-hour paper
75%
Coursework
2 assignments
25%
Module Overview
Prerequisites/Co-requisites

Completion of the progress requirements of Level HE1 and Module SE5104
Module Aims

To introduce students to basic concepts in data presentation and statistical data analysis, to enable them to analyse both technical and business data and use this information in decision-making.

Learning Outcomes

On successful completion of the module, students should be able to:

  • Select and use appropriate graphical/pictorial representation of data.
  • Calculate statistical measures associated with sample data
  • Calculate probabilities based on discrete and continuous probability distributions such as binomial, Poisson, normal, exponential.
  • Be able to construct and interpret confidence intervals .
  • Be able to formulate and conduct hypothesis testing.
  • Be able to use the above techniques in the analysis and interpretation of technological and business data, in areas such as quality control and business decision-making.
Module Content
  • Introduction to the uses of statistics
  • Introduction to data collection and sampling methods

Descriptive statistics: 

Graphical and computational to include:

  • Pictorial/graphical representation of data e.g. histograms, pie charts
  • Measures of central tendency and spread of sample data e.g. mean, median, mode, standard deviation

Probability theory:

  • Basic probability concepts
  • Discrete random variables and probability distributions: e.g. binomial, Poisson
  • Continuous random variables and probability distributions: e.g. normal, exponential

Statistical inference:

  • Sampling distributions, hypothesis testing, confidence intervals, linear regression
  • Applications to e.g. quality control, and business decision-making.
Methods of Teaching/Learning

The content will be delivered principally in lecture form supported by tutorial sessions in which use will be made of computer facilities including Excel etc for data presentation and calculations. Data and applications examples will be drawn from both business and technology areas.

24 hours lectures, 12 hours tutorial sessions (to include use of Excel in PC lab), and 64 hours independent learning.

Total student learning time 100 hours.

Selected Texts/Journals

Recommended background reading

Crawshaw J & Chambers J, A Concise Course in A-Level Statistics, 3rd ed, Stanley Thornes, 1994.

Berenson ML, Krehbiel T & Levine DM, Business Statistics: A First Course, 2nd ed, Prentice-Hall, 2000.

Required reading


None
Last Updated

15th August 2006