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 using Excel and 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
|
| Academic year 2024/25, Available to all students (SV1)
|
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 )
|
| Assessment (Further Info) |
Written Exam
60 %,
Coursework
40 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
100% coursework
40% - Individual Report
60% - Written Exam
Resit examination 100%. |
| Feedback |
1. Feedback will be provided on the assessment within agreed deadlines
2. Q&A sessions with the course organiser
3. Discussion board will allow students to pose a question which will be answered subsequently.
|
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S1 (December) | | 2:00 | | | Resit Exam Diet (August) | | 2:00 | |
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.
|
Reading List
| The core text for this course is OpenIntro Statistics 4e: https://www.openintro.org/book/os/. |
Additional Information
| Course URL |
http://www.bus.ed.ac.uk/programmes/ugpc.html |
| Graduate Attributes and Skills |
Communication, ICT, and Numeracy Skills:
After completing this course, students should be able to:
- Convey meaning and message through a wide range of communication tools, including digital technology and social media; to understand how to use these tools to communicate in ways that sustain positive and responsible relationships.
- Critically evaluate and present digital and other sources, research methods, data and information; discern their limitations, accuracy, validity, reliability and suitability; and apply responsibly in a wide variety of organisational contexts. |
| Keywords | BRM-1: Data Analysis,Sample and Surveys; Probability; Statistical Tests; Linear Regression |
Contacts
| Course organiser | Dr Nicholas Myers
Tel:
Email: Nick.Myers@ed.ac.uk |
Course secretary | Miss Jen Wood
Tel: (0131 6)50 8335
Email: J.Wood@ed.ac.uk |
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