The Data-Handling Process

The aims for this module are set into the context of the QAA Framework for Higher Education Qualifications and they relate to the SEEC level descriptors for level 5 study.

Data collection, representation and analysis play an increasingly important role in enquiry and decision-making in many fields.  It is hence important that students be aware of both the power and the limitations of the statistical process both to further their own enquiry and to be critical of conclusions based on such evidence.  This module aims to give students a critical awareness and understanding of the entire process and the ability to engage effectively in this process.

In relation to the QAA Framework for Higher Education Qualifications and the SEEC level descriptors for level 5 study, by the end of the module students should be able to:

1 specify a problem and engage in the data-handling process to solve this problem;

2 critically analyse the appropriateness of models of the data-handling process;

3 be critical of conclusions based on statistical evidence;

4 show an awareness of various broader mathematical and statistical issues.

1 models of the data handling process

2 measurement/data collection

3 principles of sampling with and without replacement; random and stratified sampling;

4 use of databases

5 data representation and description

6 probability and probability distributions

7 discrete and continuous random variables; expected values and moments; covariance and correlation; common distributions;

8 estimation of means, variances and proportions - properties of estimators; confidence limits;

9 principles of hypothesis testing - the null hypothesis and the alternative hypothesis; critical regions - one- and two-tail tests;

10 issues

- misrepresentation of data

- the scope of statistical claims

- the uses of statistical evidence in decision-making

- coincidence and superstition

- ethics of experimentation

The emphasis of the course will be on student understanding of the concepts and issues involved in data-handling, although competence in applying statistical techniques will also be expected.

Contact time:

Tutor-led overviews of the various areas and introduction to various specific techniques.  It will also involve student seminars considering the issues involved in data-handling.  A substantial proportion of contact time will involve the use of graphical calculators and the computer package Excel.

Non-contact time:

Independent student exploration by means of practical work, computer simulation and engagement with relevant literature.

Books:

Erickson, B. et al  (1992)  Understanding Data  Buckingham:  Open University Press

Francis, A.  (1986)  Advanced Level Statistics  Oxford ST(P)

Groenveld, R.  (1988)  Introductory Statistical Methods  Boston: PWS-Kent

Huff, D.  (1973)  How to Lie with Statistics  Harmondsworth: Penguin

Moore, D.  (2002)  Statistics: Concepts and Controversies  (5^TH edition)  New York: W H Freeman

Rees, D.  (1995)  Essential Statistics  London: Chapman & Hall

Walpole, R. & Freund, J. (1982)  Introduction to Statistics  London: Collier MacMillan 

Journals:

Significance:  Journal of The Royal Statistical Society

Electronic Sources: (All accessed July 2009)

Dartford College – Chance Lectures - available from www.dartmouth.edu/~chance/ChanceLecture/AudioVideo.html

Mathcentre - available from www.mathcentre.ac.uk

School home:

School of Education