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Introductory Statistical Methods (STAT0022)

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: BA Economics and Business with East European Studies - BA Language and/with Management Studies.
Timetable

Alternative credit options

There are no alternative credit options available for this module.

Description

This module aims to provide an introduction to statistical methods and interpretation of data, along with associated computing required by managers. It is intended for students registered on certain undergraduate degree programmes offered by the ÐÂÏã¸ÛÁùºÏ²Ê¿ª½±½á¹ûSchool of Slavonic and East European Studies (SSEES) and the ÐÂÏã¸ÛÁùºÏ²Ê¿ª½±½á¹ûSchool of European Languages, Culture and Society (SELCS).

Intended Learning Outcomes

  • have an understanding of basic methods of descriptive statistics, confidence intervals and significance tests, which can be appliedÌýto simple applications in business studies;
  • be able to implement these methods using appropriate computer software.

Applications - The statistical methods covered are useful in the routine analysis of scientific methods, as might be encountered in other modules.

Indicative Content - Descriptive statistics and graphical methods. Use of the normal distribution. Confidence intervals and significance tests applied to one and two sample problems by parametric and non-parametric methods. Correlation and regression. Simple time series methods (moving averages, trends, seasonality). Goodness-of-fit and contingency tables. Index numbers. Use of Stata for statistical purposes.

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
25% In-class activity
75% Coursework
Mark scheme
Numeric Marks

Other information

Number of students on module in previous year
93
Module leader
Dr Alessandra Cipriani
Who to contact for more information
stats.ugt@ucl.ac.uk

Last updated

This module description was last updated on 8th April 2024.

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