2024/25 Taught Postgraduate Module Catalogue

LUBS5902M Data Analysis in International Business

15 Credits Class Size: 90

Module manager: Dimitrios Georgakakis
Email: D.Georgakakis@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2024/25

Module replaces

LUBS5901M - Quantitative Methods for International Business

This module is not approved as an Elective

Module summary

Data plays an essential role in making business decisions and formulating policies in the global economy. This module explores how to collect and analyse international business-related data by introducing a wide range of statistical techniques and qualitative methods. Key topics include data collection, data visualization, descriptive and inferential statistics, and qualitative data analysis.

Objectives

This module examines how a wide range of statistical techniques and qualitative methods can be applied to real-world international business problems. Emphasis is placed on showing how managers and practitioners can effectively use such techniques to evaluate and enhance different aspects of firm performance and formulate policies in the global economy.

Learning outcomes

On completion of this module, students will be able to:
1. Design and critically assess the methods on collecting quantitative and qualitative data in international business.
2. Employ a wide range of quantitative methods, critically evaluate their benefits and problems, and use such techniques in practice in order to solve international business problems.
3. Visualise quantitative and qualitative data using SPSS and interpret the results.
4. Estimate and interpret the relationship between two (or more) variables through use of SPSS and critically evaluate the strategic importance of the findings in international business decision-making.

Skills outcomes

Learn to select and apply the appropriate statistical techniques to solve certain problems while using statistical software and interpret the results.

Syllabus

Data basics and visualisation; Measures of central location and dispersion; Descriptive statistics and correlation; Linear regression; Hypothesis testing; OLS assumptions; Logistic regression; Sampling and quantitative data collection; Qualitative data collection; Qualitative data analysis.

Teaching Methods

Delivery type Number Length hours Student hours
Workshop 5 2 10
Lecture 11 2 22
Private study hours 118
Total Contact hours 32
Total hours (100hr per 10 credits) 150

Private study

This could include a variety of activities, such as reading, watching videos, question practice and exam preparation.

Opportunities for Formative Feedback



The teaching methods could include a variety of delivery models, such as face-to-face teaching, live webinars, discussion boards and other interactive activities. There will be opportunities for formative feedback throughout the module, such as in-class quiz, after-class exercises, and mock exam.

Exams
Exam type Exam duration % of formal assessment
Standard exam (closed essays, MCQs etc) 2.0 Hrs Mins 100
Total percentage (Assessment Exams) 100

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading List

The reading list is available from the Library website

Last updated: 11/18/2024

Errors, omissions, failed links etc should be notified to the Catalogue Team