| CODE | EMA3001 | ||||||||
| TITLE | Statistical Design and Tools for Business | ||||||||
| UM LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||||
| MQF LEVEL | 6 | ||||||||
| ECTS CREDITS | 4 | ||||||||
| DEPARTMENT | Faculty of Economics, Management and Accountancy | ||||||||
| DESCRIPTION | This study-unit provides a good overview of the basis of traditional research methods within a real organizational environment and introduces the scope and methods for analysing problems and challenges prior to providing evidence-based solutions. The study-unit also attempts to link these techniques with practical issues. Furthermore, this study-unit focuses on how participants can use MS Excel and SPSS to conduct a statistical analysis of the data and to report/communicate the findings. More specifically, this unit will delve into data organisation and exploration procedures, summarising data, graphing data, describing relationships, and mainstream statistical inference techniques generally covered in undergraduate business and management courses. Study-Unit Aims: This study-unit aims to develop the students' capability to conduct a statistical analysis of data, to draw conclusions from the data analysis and to communicate these effectively verbally and in writing. Rather than focusing on laborious calculations (as in the case of the pre-requisite study unit), MS Excel and SPSS will be used as tools for teaching statistical concepts. Learning Outcomes: 1. Knowledge & Understanding: By the end of the study-unit the student will be able to: - Define Sampling techniques - Carry out Graphical representation in SPSS - Carry out Graphical representation in Excel - Work with the Excel data analysis tool pack - Carry out Basic Statistical Analysis techniques (SPSS AND EXCEL) - Define Confidence Intervals (SPSS AND EXCEL) - Define Means testing and tests for associations (t-test, ANOVA, Chi-Squared test and other statistical tests) - Define Parametric and Non-Parametric tests - Define Linear Regression Analysis (incl. predictions) - Define Multiple Regression Analysis 2. Skills: By the end of the study-unit the student will be able to: - Apply various Sampling techniques - Apply graphical data analysis in SPSS - Understand Graphical representation in Excel - To work out data analysis using the Excel data analysis tool pack - Apply basic statistical data analysis techniques (SPSS AND EXCEL) - Apply confidence Intervals (SPSS AND EXCEL) - Apply means testing and tests for associations (t-test, ANOVA, Apply Chi-Squared test and other statistical tests) - Apply Parametric and Non-Parametric tests - Apply linear Regression Analysis (incl. predictions) - Apply multiple Regression Analysis Main Text/s and any supplementary readings: Main Texts: - Saunders, M., Lewis, P & Thornhill, A. (2012). Research Methods for Business Students (6th edition), Harlow: Pearson. Supplementary Readings: - Monippally, M.M. and Pawar, B.S., (2008). Academic writing: A guide for management students and researchers. SAGE Publications India. - Alvesson, M., & Sandberg, J. (2013). Constructing research questions: Doing interesting research. Sage. |
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| ADDITIONAL NOTES | Pre-requisite Study-unit: EMA1100 | ||||||||
| STUDY-UNIT TYPE | Lecture | ||||||||
| METHOD OF ASSESSMENT |
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| LECTURER/S | Jirka Konietzny Vincent Cassar Daniela Castillo Vincent Marmara |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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