Course Information Undergraduate prospectus

Quantitative Methods in International Business

Course summary

Course code: STAT1036
Level: 5
Credits: 15
School: Business Faculty
Department: International Bus and Economics
Course Coordinator(s): Guido Conaldi

Specification

Aims

The course aims to provide students with the skills and capabilities necessary to critically analyse research results as well as to conduct independent research in the areas of business and management. The course explores the nature of business and management research so to raise the awareness of the need not to take evidence found in various sources online and offline for granted. The course covers a selection of relevant research methods, both qualitative and quantitative, among the most ubiquitous in the business literature.

Learning outcomes

On successful completion of this course a student will be able to:

1 increase awareness of the role of statistics as a business decision-making tool
2 begin to analyse (formally) numerical data using a spreadsheet editor
3 use a spreadsheet editor to solve various statistical problems by applying basic statistics principles and techniques
4 explore and reflect on basic statistical problems and fallacies relevant for business management
5 present effectively numerical and statistical data
6 interpret and synthesize quantitative information, organise data and information into knowledge and present outcomes effectively in various formats

Indicative content

This course will delve into the foundations of quantitative methods for the analysis of business data. The course will provide students with the foundations of what is an indispensable toolbox for researchers and managers alike. Throughout the course students will study how to catalogue and analyse business data to help inform business decisions.
PART 1: Numerical Skills Revision
1.1 Solving algebraic problems with spreadsheet editor
1.2 Financial indexes and functions with spreadsheet editor
1.3 Coordinate geometry
PART 2: Visualising and Presenting Data
2.1 Representing data variables in a spreadsheet editor
2.2 Graphical representation of data
PART 3: Descriptive Statistics
3.1 Measures of central tendency
3.2 Measures of dispersion
3.3 Exploratory data analysis in a spreadsheet editor
PART 4: Probability and Sampling Distributions
4.1 Introduction to Probability: basic definitions and paradoxes
4.2 Sampling from a population
4.2 Point estimates and confidence intervals
PART 5: Introduction to Hypothesis Testing
5.1 Hypothesis testing rationale
5.2 Tests for differences of population means
5.3 Non-parametric hypothesis testing

Teaching and learning activity

The course will bring together lecture and laboratories. Attendance to both is essential. During lectures students will be exposed to the main theoretical concepts and ideas at the base of quantitative analysis. During the laboratories, through the use of cases and by performing some tasks using a specific software, students will put the ideas covered during the lectures in practice. The course is organised as a mixture of lectures, tutorials, self-managed exercises and guided readings. The students are expected to attend formal classes and to carry out tutorial activities individually in order to discuss the main statistical techniques introduced. Guest lecturers will be used as needed to enrich student learning and ascertain currency of student experience.

Assessment

Exercises - 60% weighting, 40% pass mark.
Learning outcomes 1, 2, 3, 5, 6.
Outline Details - Students will answer a set of close-ended questions on topics covered during previous lectures and in the corresponding textbook chapters. The questions will be available on Moodle only during the designated tutorial sessions as this activity will also represent the active engagement of the student.
Students will carry out an assignment with multiple exercises in Excel on the topics covered in the course and in the relevant Chapters in the textbook. An Excel file with the exercises will be provided on Moodle in advance of the deadline. Students will upload a copy of the file on Moodle once having completed the exercises. Excel assignments will each award a predefined number of points that will be converted to a conventional mark according to a marking scheme that will be available on Moodle in advance of the submission deadlines.

Exam - 40% weighting, 40% pass mark.
Learning outcomes 1, 4, 6.
Outline Details - Students will answer questions and will be asked to interpret results based on the topics covered in the course. A mix of close-ended and open-ended questions will be provided.

Students are not required to pass all elements of assessment in order to pass the course.