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CSC-10052 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

For academic year: 2024/25 Last Updated: 04 March 2025

CSC-10052 - Making Sense of Statistics for Data Scientists
Coordinator: Allison Gardner Tel: +44 1782 7 33989
Lecture Time: See Timetable...
Level: Level 4
Credits: 15
Study Hours: 150
School Office: 01782 733075

Programme/Approved Electives for 2024/25

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2024/25

This module provides an introduction to common techniques for exploring, summarising and modelling data. The module develops transferable skills through solving problems, modelling and using spreadsheets to handle quantitative information. Emphasis is placed on understanding the meaning behind the data and on the importance of the correct presentation of findings.

Aims
The aim of this module is to prepare learners to understand of some of the more common statistical techniques, to encourage good practice and highlight common errors and misconceptions. Key to this module is to provide a differentiated learning framework for apprentices, some of whom may not have had significant mathematical and statistical education beyond Level 2 whilst others may have level 3 or higher mathematics background.
Specifically, the module aims to develop:
1) a sound knowledge of mathematical concepts, skills and techniques important in the use of data science.
2) confidence in applying mathematical and statistical thinking and reasoning in a range of new and unfamiliar contexts to solve real-life problems;
3) competency in interpreting and explaining solutions of problems in context;
4) fluency in procedural skills, common problem-solving skills and strategies.

Talis Aspire Reading List
Any reading lists will be provided by the start of the course.
http://lists.lib.keele.ac.uk/modules/csc-10052/lists

Intended Learning Outcomes

apply appropriate graphical techniques to summarise data;: 1,2
apply mathematical and statistical thinking and reasoning in a range of new and unfamiliar contexts to solve real-life problems;: 2
interpret and explain solutions of a problem in a given context;: 2
identify the correct, and incorrect, ways of presenting data;: 1,2
interpret, in time-constrained conditions, data and draw suitable conclusions: 1

Study hours

22 hours lectures (delivered online)
11 hours examples activities delivered either online or during block release tutorial sessions
24 hours course work preparation
93 hours private study


School Rules

None

Description of Module Assessment

1: Coursework weighted 40%
Three short timed online tasks


2: Assignment weighted 60%
Assignment


The University undertakes a continuous review of its teaching and research provision to ensure programmes are of a high quality and changes may be made to modules where it is necessary and reasonable to do so. Please be aware that minor changes to modules, such as a change to an individual assessment, can occur up until enrolment, although we endeavour to give you as much notice as possible of any changes. Details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/legalgovernancecompliance/governance/actcharterstatutesordinancesandregulations/studenttermsconditions/

Last Updated: 04 March 2025