Undergraduate Course: Business Research Methods I: Introduction to Data Analysis (BUST08033)
||College||College of Humanities and Social Science
|Credit level (Normal year taken)||SCQF Level 8 (Year 2 Undergraduate)
||Availability||Available to all students
|Summary||In modern management it is important to be numerate. The objective of this course is to give the student an appreciation and an ability to employ Quantitative Techniques used in Business and Management Research. (This course formerly entitled Business Research Methods I: Quantitative Techniques CMSE08002.)
All Business Management students require the ability to deal with quantitative material, including the collection, collation and analysis of such data. This course introduces students to the quantitative techniques in business mainly centred on statistical aspects. It also provides them with experience in designing questionnaires and report writing. In order to effectively carry out statistical analysis, the students are required to have experience of computing. This course reinforces the experience gained in their Computing for Business course taken in Year 1.
- Types and Sources of Data
- Samples and Surveys
- Exploratory Data Analysis
- Probability, Estimation and Sampling Distributions
- Hypothesis Testing
- Non-Parametric Hypothesis Testing
Student Learning Experience
The course is delivered through lectures, tutorials, computing session, problem-solving sessions and self-experiential learning. The lectures provide the concepts of the techniques for collection, presentation and analysis of data. The tutorials reinforce the use of the techniques through examples and discussion. The computing session allows the student to explore the use of software to apply the techniques. The student will gain valuable further understanding and experience through reading the appropriate sections in the suggestion text and through the coursework.
Information for Visiting Students
|Pre-requisites|| Visiting students should usually have at least 1 introductory level Business Studies course at grade B or above (or be predicted to obtain this) for entry to this course. We will only consider University/College level courses.
|High Demand Course?
Course Delivery Information
|Academic year 2017/18, Available to all students (SV1)
|Learning and Teaching activities (Further Info)
Lecture Hours 30,
Seminar/Tutorial Hours 4,
Supervised Practical/Workshop/Studio Hours 7,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework 30% (1000-word report plus survey); Final examination 70%. Resit examination 100%.
||1. Generic feedback on your COURSEWORK, together with individual marks, will be available on Learn within 15 working days from the submission deadline and you will be able to review your individual feedback electronically via Grademark on Learn.
2. The TUTORIALS provide the opportunity for testing your understanding and getting direct feedback. The tutorial exercises are posted in the 'Tutorials' folder on Learn and students are expected to complete the exercises before the tutorial so that any problems can be discussed at the tutorial.
3. The non-compulsory PROBLEM SOLVING SESSIONS at the end of Weeks 4-10 provide the opportunity for testing your understanding of the week's lectures and getting direct feedback. The Problem Solving Session exercises are posted in the 'Problem Solving Sessions' folder on Learn and students are expected to complete the exercises before the session so that any problems can be discussed at the session.
4. Your EXAMINATION marks will be posted on Learn (together with generic feedback and examination statistics) as soon as possible after the Boards of Examiners' meeting (normally end of January/beginning of February). You will have the opportunity to look at your examination scripts in early February in the Business School UG Office Reception (Room 1.11, Business School, 29 Buccleuch Place). Note that non-Honours students will be notified of the arrangements to collect examination scripts from the UG Office, normally following the retention period.
||Hours & Minutes
|Main Exam Diet S1 (December)||2:00|
|Resit Exam Diet (August)||2:00|
On completion of this course, the student will be able to:
- Describe basic statistical techniques for data collection, presentation and analysis.
- Critically review the collection, presentation and analysis of data.
- Understand and explain how to tackle business problems through the use of statistical techniques.
- Apply statistical techniques to data.
- Discuss the results of the application of statistical techniques to data in written reports and oral presentation.
|Recommended book for the course: Michael Barrow, Statistics for Economics, Accounting and Business Studies Longman, London & New York, Chapters 1-6.|
Optional useful reading on surveys and data collection for the coursework assignment:
1. Kent, R., Marketing Research: Approaches, Methods and Applications, 2007, London: Thomson Learning, Part II.
2. Bradley N., Marketing Research: Tools & Techniques, 2007, Oxford University Press, Part 2.
2. Hair J.F., Bush R.P., Ortinau D.J., Marketing Research, 2003 (2nd ed.), McGraw-Hill, Chapters 8,9,11,13,14.
3. Malhotra, N.K., Birks D.F., Marketing Research: an applied approach, 2006, FT Prentice Hall, Chapters 3,7,8,10,12,13,14.
4. Sekaran U., Bougie R. Research Methods for Business, 2010 (5th ed.) Wiley, Chapters 6,7,8,10.
|Graduate Attributes and Skills
||Subject Specific Skills
On completion of the course the students should be able to:
a) Develop their skills to collect, present and analyse data.
b) Develop their ability to design questionnaires.
On completion of the course the students should be able to:
a) Demonstrate their ability to carry out quantitative analysis of data.
b) Demonstrate their ability to use software to obtain analysis of data.
c) Demonstrate their ability to collect data through design of questionnaire.
|Additional Class Delivery Information
||Three 1-hour lectures in Weeks 1-5, 7-11;
One 1-hour Friday Problem Session in Weeks 4-5, 7-11 optional;
1-hour tutorials in Weeks 3, 5, 9;
1-hour computer lab in Week 11.
|Keywords||BRM-1: Data Analysis
|Course organiser||Prof Jake Ansell
Tel: (0131 6)50 3806
|Course secretary||Ms Patricia Ward-Scaltsas
Tel: (0131 6)50 3823