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Module

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 StudyAssessment preparation and completion175:0075:00N/A
Scheduled Learning And Teaching ActivitiesLecture122:0024:00pip lectures
Guided Independent StudyDirected research and reading120:0020:00N/A
Scheduled Learning And Teaching ActivitiesSmall group teaching32:006:00pip seminars
Structured Guided LearningStructured non-synchronous discussion40:302:002 per semester
Scheduled Learning And Teaching ActivitiesDrop-in/surgery41:004:001 for whole cohort intro, 1 for pre-assessment clinic, 2 for drop-in (1 per semester)
Guided Independent StudyIndependent study169:0069:00N/A
Total200:00
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
Report2A1004000 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 exercises2MN/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