DATA ANALYSIS SKILLS

SHE Level 1
SCQF Credit Points 20.00
ECTS Credit Points 10.00
Module Code M1N120382
Module Leader n/a
School Glasgow School for Business and Society
Subject Economics
Trimesters
  • A (September start)
  • B (January start)

Summary of Content

The module aims to provide students with a foundation of business, analytical and learning skills for personal, academic and career development. The objective of the module is to enhance students' numeracy, data collection and analysis, information technology, and problem solving skills for business and academic application. The module is designed to equip students with the skills necessary to understand, comprehend and analyse quantitative and qualitative data as employed in the public, private and voluntary sectors for business, operational, financial and/or strategic decision making. Furthermore, the module aims to provide students with the understanding and constructs of theory as a foundation of academic learning and for its business application.

Syllabus

Introduction to data analysis, business and data theory, introduction to primary and secondary data, data generation and collation, data management and organization, introduction to basic data operations, basic survey design, evaluating data (formulae and functions), data presentation (charts, financial planning) Basic statistical terminology and analysis.

Learning Outcomes

On successful completion of this module students should be able to: Demonstrate business and analytical skills for academic, personal and career development. Understand, comprehend and analyse business data as presented in various forms. Use information technology and software packages for business applications. Use various skills and techniques to collect and analyse quantitative and qualitative data. Understand applicability of theory and ability to communicate arguments and ideas in various formats and contexts.

Teaching / Learning Strategy

The module is delivered through several modes of contact and independent learning. The modes of learning over twelve weeks will include: lectures, seminars and lab practicals. The weekly lectures will introduce students to qualitative and quantitative data analysis. The lab practicals will involve instruction on sourcing and generating primary and secondary data, basic statistical terminology and methods, the use of software packages to collate and analyse qualitative and quantitative data, development of an independent archive of references, the development of surveys, and the applicability of data in an academic, employment and business context. There will be additional lab sessions to review and consolidate lab practicals. The independent lab sessions will focus on the consolidation of supervised lab practicals. Seminars will build on students' academic skills in understanding academic literature, writing essays and reports. The students' directed and independent learning will be supported by online modes of learning through GCU Learn. Students will be engaged in independent and directed learning towards the completion of a lab test and portfolio of learning.

Indicative Reading

-720 essential Reading: Miller K.J. and Gasteen A., (2011) Data Analysis Skills, Harlow, Pearson. Additional Reading: -284 O Dochartaigh, N. (2012) Internet Research Skills . 3rd Ed.London: Sage. -284 Albright, S.C., Winston, W. & Zappe, C. (2009) Data Analysis and Decision Making with Microsoftae Excel , Oxford, Oxford University Press. -284 Anderson, D. R., Sweeney, D.J. & Williams, T.A. (2009) Essentials of Modern Business Statistics, 4th Edition, Oxford: Oxford University Press. Bryman, A. and Bell, E. (2011) Business Research Methods , Oxford: Oxford University Press. Burton, S. & Shelton, N. (2005) Practical Math Applications , 2nd Edition, Oxford: Oxford University Press Cameron, S. (2009) The Business Student's Handbook , Harlow: Prentice Hall. Collis, J and Hussey, R. (2009) Business Research , Basingstoke: Palgrave Macmillan. Cottrell, S. (2005) Critical Thinking Skills: Developing Effective Analysis and Argument , Basingstoke: Palgrave. Davis, G. & Pecar, B. (2010) Business Statistics , Oxford, Oxford University Press. -284 Easterby-Smith, M., Thorpe, R., Jackson, P. & Lowe, A. (2008) Management Research, London: Sage. Lee, N. & Lings, I. (2008) Doing Business Research: A Guide to Theory and Practice. London: Sage Levine, D. M., Stephan, D. F., Krehbiel, T. C. & Berenson, M. L. (2011), Statistics for Managers , 6 th Edition, Pearson, New Jersey. Locke L. F., Silverman S. J. and Spirduso W.W. (2009) Reading and understanding research, 3 rd ed. California, Sage Publications Inc. Manzo, J.M. (2007) Information and Data Analysis, Harlow: Persons Education Ltd. -284 Oakshott, L. (2009) Essential Quantitative Methods, Basingstoke: Palgrave Macmillan. -284 Saunders, M., Lewis, P. & Thornhill, A. (2009) Research Methods for Business Students. Harlow: Prentice-Hall. Taylor, S. (2007) Business Statistics , Basingstoke: Palgrave Macmillan. Weiers, R.M. (2008) Introductory Business Statistics, 7 th ed., South-Western Cengage Learning.

Transferrable Skills

Personal and Career Development Skills: numeracy; data sourcing, organisation, analysis and presentation; problem solving and understanding theoretical application. Self Management and Organisation: managing time and tasks; and data organisation. Communication: Oral and written skills are developed through directed learning, participation in academic discussions, creation of a personal, reflective online journal and through assessment strategies. Learning: A range of cognitive, reflective and applied skills are the basis of learning for this module. Applied reasoning is developed in directed and independent learning. Data Gathering, Manipulation and Presentation: These skills are core to the aims of the module and are developed as students are directed through lab practical exercises. A range of skills are developed such as: sourcing data from various resources; developing library skills to find and organise information and data; analyse and present data (with the utilisation of information technology and application packages such as Excel and RefWorks); and the preparation of assessments.

Module Structure

Activity Total Hours
Practicals (PT) 48.00
Independent Learning (FT) 73.00
Assessment (PT) 70.00
Assessment (FT) 70.00
Practicals (FT) 48.00
Independent Learning (PT) 73.00
Lectures (FT) 9.00
Lectures (PT) 9.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 2 n/a 50.00 35% Portfolio of Learning consisting of research lab exercises
Coursework 1 2.00 50.00 35% In-Lab Assessment