Foundation Statistics - MAST0025

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Module delivery information

Location Term Level1 Credits (ECTS)2 Current Convenor3 2022 to 2023
Combined Autumn and Spring Terms 3 15 (7.5) Oscar Rodriguez de Rivera Ortega checkmark-circle


Statistical techniques are a fundamental tool in being able to measure, analyse and communicate information about sets of data. Using illustrative data sets we show how statistics can be indispensable in applied sciences and other quantitative areas. This module covers the basic methods used in probability and statistics using Excel for larger data sets. A more detailed indication of the module content follows.

Sampling from populations. Data handling and analysis using Excel. Graphical representation for the interpretation of univariate and bivariate data; outliers. Sample summary statistics: mean, variance, standard deviation, median, quartiles, inter-quartile range, correlation. Probability: combinatorics, conditional probability, Bayes' Theorem. Random variables: discrete, continuous; expectation, variance, standard deviation. Discrete and continuous distributions: Binomial, discrete uniform, Normal, uniform. Sampling distributions for the mean and proportion. Hypothesis testing: one sample, mean of Normal with known variance and proportion, 1- and 2-tail. Confidence intervals: one sample, mean of Normal with known variance and population proportion.


Contact hours

Total contact hours: 48
Private study hours: 102
Total study hours: 150

Method of assessment

80% examination, 20% coursework

Indicative reading

Understandable statistics: concepts and methods, Brase, C.H. and Brase, C.P., Brooks/Cole, 2017, ISBN 9781337119917
Statistics with Microsoft Excel, Fourth edition, Dretzke, B.J., Pearson/Prentice Hall, 2009, ISBN 9780136043874

See the library reading list for this module (Canterbury)

Learning outcomes

The intended subject specific learning outcomes. On successfully completing the module students will be able to:

1 demonstrate understanding of the basic body of knowledge associated with elementary probability and statistics;
2 demonstrate the capability to solve problems in accordance with the basic theories and concepts in the following areas, whilst demonstrating a reasonable level of skill in
calculation and manipulation of the material: interpretation of data, conditional probability, discrete and continuous probability distributions, hypothesis testing and confidence
3 apply the basic techniques associated with hypothesis testing and confidence intervals in several well-defined contexts;
4 make appropriate use of Excel;
5 demonstrate a proficiency in probability and statistics suitable for Stage 1 entry.

The intended generic learning outcomes. On successfully completing the module students will be able to:

Demonstrate an increased ability to:

1 manage their own learning and make use of appropriate resources;
2 understand logical arguments, identifying the assumptions made and the conclusions drawn;
3 communicate straightforward arguments and conclusions reasonably accurately and clearly;
4 manage their time and use their organisational skills to plan and implement efficient and effective modes of working;
5 solve problems relating to qualitative and quantitative information;
6 make use of information technology skills such as spreadsheet use, online resources (Moodle), internet communication.
7 demonstrate an increased level of skill in numeracy and computation.


  1. Credit level 3. Foundation level module taken in preparation for a degree.
  2. ECTS credits are recognised throughout the EU and allow you to transfer credit easily from one university to another.
  3. The named convenor is the convenor for the current academic session.
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