NBS8002 : Techniques for Data Analysis
- Offered for Year: 2024/25
- Module Leader(s): Dr Bo Che
- Owning School: Newcastle University Business School
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
| Semester 1 Credit Value: | 10 |
| Semester 2 Credit Value: | 10 |
| ECTS Credits: | 10.0 |
| European Credit Transfer System | |
Aims
• To introduce a broad range of underlying concepts and methodologies that are used in the data analytics process.
• To enable students to employ various analytical techniques that support effective decision-making in today’s increasingly competitive market. Students will also be equipped to appraise a wide range of applications and techniques for collecting, visualising, organising and analysing financial data that are designed to help financial analysts and other information users to improve their decision-making.
• To enable students to transform, analyse and interpret data, delivering solutions for theevaluation of investment opportunities in the financial sector.
Outline Of Syllabus
1. Descriptive statistics, visualising, organising and presenting data using appropriate tables, diagrams and numerical measures.
2. Basic probability theory and its applications, manipulations of proabilities applying various rules.
3. Referential statistics, sampling, estimation, hypothesis testing.
4. Regression, econometric modelling, autocorrelation, heteroscedasticity, multicollinearity.
5. Event study, literature review, methodology review, research design.
6. Challenges faced by modern financial data analysis in the context of emerging ‘big data’ society.
NB: The programme assumes no prior experience of statistics.
Teaching Methods
Teaching Activities
| Category | Activity | Number | Length | Student Hours | Comment |
|---|---|---|---|---|---|
| Guided Independent Study | Assessment preparation and completion | 1 | 75:00 | 75:00 | N/A |
| Scheduled Learning And Teaching Activities | Lecture | 12 | 2:00 | 24:00 | pip lectures |
| Guided Independent Study | Directed research and reading | 1 | 20:00 | 20:00 | N/A |
| Scheduled Learning And Teaching Activities | Small group teaching | 3 | 2:00 | 6:00 | pip seminars |
| Structured Guided Learning | Structured non-synchronous discussion | 4 | 0:30 | 2:00 | 2 per semester |
| Scheduled Learning And Teaching Activities | Drop-in/surgery | 4 | 1:00 | 4:00 | 1 for whole cohort intro, 1 for pre-assessment clinic, 2 for drop-in (1 per semester) |
| Guided Independent Study | Independent study | 1 | 69:00 | 69:00 | N/A |
| Total | 200:00 |
Teaching Rationale And Relationship
The syllabus requires students to master a wide range of statistical skills. Students are also expected to understand the concepts underlying the application of statistical tools and evaluate their limitations. Helping students achieve this competence is best achieved by the combination of lecture materials, seminars, online discussions on Canvas, and guided independent studies. The fully blended approach was taken as it offers the flexibility we need to prepare for the uncertain future.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
| Description | Semester | When Set | Percentage | Comment |
|---|---|---|---|---|
| Report | 2 | A | 100 | 4000 words - using statistical analysis of real data, examine impact of firm-specific information on a company’s stock returns. |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
| Description | Semester | When Set | Comment |
|---|---|---|---|
| Prob solv exercises | 2 | M | N/A |
Assessment Rationale And Relationship
There is one project, involving statistical analysis of financial data, including the presentation of data, development of a regression model for an event study, time series analysis and forecasting.
The objective of the report is to examine, using statistical analysis of real data, the impact of firm-specific information on a company’s stock returns. To complete the assignment, students are expected to undertake three types of activities: 1) Selecting a public company for analysis, collecting relevant data, and reviewing literature; 2) Performing appropriate analysis of the impact of multiple information events on the stock returns of a public company; 3) Writing up a report describing your research design and interpreting your research results.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- NBS8002's Timetable