Undergraduate Course: Business Research Methods I: Introduction to Data Analysis (BUST08033)
Course Outline
| School | Business School |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| 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. |
| Course description |
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. Guidance will be given in using SPSS.
Syllabus
- Types and Sources of Data
- Samples and Surveys
- Exploratory Data Analysis
- Probability, Estimation and Sampling Distributions
- Hypothesis Testing
- Non-Parametric Hypothesis Testing
- Correlation
- Regression
Student Learning Experience
The course is delivered through lectures, problem-solving sessions, discussion boards 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 student will gain valuable further understanding and experience through reading the appropriate sections in the suggestion text and through the coursework.
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Information for Visiting Students
| Pre-requisites | Visiting students must have at least 1 introductory level Business Studies course at grade B or above for entry to this course. We will only consider University/College level courses. |
| High Demand Course? |
Yes |
Course Delivery Information
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| Academic year 2022/23, Available to all students (SV1)
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Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
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
153 )
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| Assessment (Further Info) |
Written Exam
60 %,
Coursework
40 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
The assessment for this course is based on Coursework (accounting for 40% of the course result) in the form of an individual report which will include:
a) Survey and Sampling accounting for 40%,
b) Questionnaire accounting for 20% and
c) Summary and Descriptive Statistics accounting for 40%
The examination for BRM I will count for 60%.
Resit examination 100%. |
| Feedback |
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. PROBLEM SOLVING SESSIONS at the end of Weeks 1-10 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.
3. Discussion board will allow students to pose a question which will be answered subsequently.
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 May/beginning of June). You will have the opportunity to look at your examination scripts in early June 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.
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| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
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| Main Exam Diet S1 (December) | | 3:00 | | | Resit Exam Diet (August) | | 3:00 | |
Learning Outcomes
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.
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Reading List
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. |
Additional Information
| Course URL |
http://www.bus.ed.ac.uk/programmes/ugpc.html |
| 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.
Key Skills
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.
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| Additional Class Delivery Information |
Three lectures in Weeks 1-10;
One Friday Problem Session in Weeks 1-10 optional; Discussion board will retain questions and answers that have been posed. |
| Keywords | BRM-1: Data Analysis,Sample and Surveys; Probability; Statistical Tests; Linear Regression |
Contacts
| Course organiser | Prof Jake Ansell
Tel: (0131 6)50 3806
Email: |
Course secretary | Ms Chrysanthi Manidou
Tel: (0131 6) 50 3826
Email: |
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