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Introduction to Practical Statistics (STAT0004)

Key information

Faculty
Faculty of Mathematical and Physical Sciences
Teaching department
Statistical Science
Credit value
15
Restrictions
This module is only available to students registered on the following degree programmes: Affiliate Statistics - BSc Data Science - BSc(Econ) Economics and Statistics - BSc/MSci Mathematics and Statistical Science - BSc Statistics - BSc Statistics and Management for Business - BSc Statistics, Economics and Finance - BSc Statistics, Economics and a Language - MSci Statistical Science (International Programme).
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module aims to provide training in the basic skills of practical statistics using a statistical software package. Together with STAT0002 and STAT0003, it provides the foundation for further study of statistics to students on the undergraduate degree programmes offered by the Department of Statistical Science (including the MASS programmes).ÌýFor these students, the academic prerequisites for this module are satisfied via successful admission to their programme.

Intended Learning Outcomes

  • be able to use the R statistical software package for data analysis and simulation;
  • be able to identify and carry out an appropriate statistical analysis of a simple data set using a computer;
  • be able to interpret the output from a statistical software package when used for simple statistical analyses.

Applications - Modern statistical analysis in practice is almost entirely computer-based, and statistical software packages are widely used in all areas of quantitative investigation. The R package is widely used and extremely powerful, thereby providing students with a solid basis for using other packages in a wide variety of application areas.

Indicative Content - Practical application of the methods taught in STAT0002 and STAT0003, in workshops. Use of the R statistical computing package for data analysis and simulation.

Key Texts - Available from .

Module deliveries for 2024/25 academic year

Intended teaching term: Terms 1 and 2 ÌýÌýÌý Undergraduate (FHEQ Level 4)

Teaching and assessment

Mode of study
In person
Methods of assessment
75% Coursework
25% In-class activity
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
241
Module leader
Professor Ioanna Manolopoulou
Who to contact for more information
stats.ugt@ucl.ac.uk

Last updated

This module description was last updated on 19th August 2024.

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