2017/18 Undergraduate Module Catalogue

LUBS1180 Understanding Data in the Social Sciences

10 creditsClass Size: 40

Module manager: Danat Valizade
Email: D.Valizade@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2017/18

Pre-requisite qualifications

GCSE Maths - Grade B or above

This module is mutually exclusive with

LUBS1270	Statistics for Economics and Business 1
LUBS1280	Mathematical Economics
MATH0111	Elementary Diff Calculus 1
MATH0212	Elementary Integral Calculus (Version 1)
MATH0360	Introduction to Applied Mathematics 1
MATH0365	Foundation Probability and Statistics
MATH0370	Introduction to Applied Mathematics 2
MATH0380	Foundation Applied Mathematics for Business
MATH1050	Calculus and Mathematical Analysis
MATH1400	Modelling with Differential Equations

This module is approved as a discovery module

Module summary

Numbers and data are everywhere in business, management and the social sciences. We see them in the news, in marketing and advertising, in politics, and increasingly in social media. As such, skills in interpreting quantitative data are highly sought after by employers in all sectors.This module will help you develop your data literacy skills and give you a critical eye for assessing statistical claims, and the analysis of quantitative data. Through a problem based approach, focusing on particular issues in business, management and the social sciences, you will develop your skills in understanding and interpreting data from simple descriptive representation of data, to the use of graphs, to bivariate analysis and confidence testing.The module aims to ensure that every student has the confidence to use quantitative methods should they want to; hence the emphasis is on understanding and interpretation with less focus on calculation than would be found in a traditional quantitative methods module.

Objectives

The objectives of this module are to develop students’ data literacy skills. In the social sciences, it essential to be able to assess statistical claims and recognise the merits and limitations of quantitative data. Through a focus on particular issues in business, management and the social sciences, this module will give students skills in understanding and interpreting data from simple descriptive representation of data, to the use of graphs, to bivariate analysis and confidence testing.

This module is being developed as part of the Nuffield Foundation’s Q-Step initiative, to increase the number of quantitatively-skilled social science graduates. The University of Leeds is one of only fifteen universities across the UK to establish a Q-Step Centres that is supporting the development and delivery of specialist undergraduate modules, pathways and placements to improve quantitative skills in social science undergraduate degrees. This module aims to ensure that every student has the confidence to use quantitative methods should they want to. It will also open up progression to other modules in level 2 and 3 which will build on the quantitative skills acquired in this module.

Learning outcomes
Upon completion of this module, students will be able to:
- discuss the value of quantitative approaches to solving a wide range of business, management and social science issues;
- identify how quantitative data is used within business, management and the social sciences;
- recognise the limitations of quantitative data;
- use quantitative data and be able to critique the analysis of others
- identify and apply basic methods of data and statistical analysis to a range of business, management and social science issues;
- apply basic data literacy skills to practical analysis of datasets.

Skills outcomes
Upon completion of this module students will be able to:

Transferable:
- use the quantitative skills required to allow potential progression onto modules that require or benefit from possession of quantitative skills and knowledge.

- Subject specific:communicate their analysis of quantitative data to a lay audience.

Syllabus

Indicative content:

The use of quantitative data in business, management and the social sciences

Big Data and its uses in business, management and the social sciences

Working with numbers – describing and presenting data in business, management and the social sciences, to include descriptive data, averages

What do your numbers mean – generalising from a sample to a wider population, to include probability hypothesis testing, confidence intervals

Interpreting relationships between variables – correlation, regression and forecasting

Looking at differences between groups

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	10	1.00	10.00
Seminar	11	1.00	11.00
Private study hours			79.00
Total Contact hours			21.00
Total hours (100hr per 10 credits)			100.00

Private study

Students are expected to spend significant time outside of lectures checking their learning of techniques introduced in lectures, practising questions which require them to interpret quantitative data and preparing their answers to seminar questions.

Opportunities for Formative Feedback

Formative feedback based on tutorial exercises
MCQ tests giving instant feedback

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Report	2000 words	100.00
Total percentage (Assessment Coursework)		100.00

The resit for this module will be 100% by coursework.

Reading list

The reading list is available from the Library website

Last updated: 06/03/2018

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