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Module

MAR8085 : Research Skills (Inactive)

  • Inactive for Year: 2024/25
  • Module Leader(s): Dr Yongchang Pu
  • Lecturer: Mr David McGeeney
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 2 Credit Value: 10
ECTS Credits: 5.0
European Credit Transfer System

Aims

This module aims to:
(1) introduce the underlying ideas and concepts associated with research methodologies, the ethics and
philosophy of science.
(2) equip students with a basic capability in understanding and using common statistical concepts and
techniques.
(3) learn Python programming language and its application to various research scenarios.
(4) enable students to understand machine learning techniques and its applications to research in engineering.

Outline Of Syllabus

Research Skills; Research objectives; research ethics.

Statistics; data summary and data presentation. Basic concepts of probability. The rationale behind sampling, randomisation and sampling strategies. Discrete distributions; binomial and Poisson.
Continuous distributions; normal and exponential. Estimation. The central limit theorem. Confidence intervals for means using the t-distribution. Approximate confidence intervals for proportions using a normal approximation. Hypothesis testing; basic ideas and concepts.

Interrelationships between testing and confidence intervals. Tests on means and proportions. X2 goodness of fit tests. Analysis of contingency tables. Correlation and regression. Practical classes will be based on the statistical package MINITAB. Multiple regression analysis (MRA) & principle component analysis (PCA) using PRIMER software. Modelling and simulation software.

Python programming language and its application to various research scenarios.

Machine learning techniques and its applications to research in engineering.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Scheduled Learning And Teaching ActivitiesLecture121:0012:00Present-in-person lectures
Guided Independent StudyAssessment preparation and completion111:0011:00Open Book Assignment
Guided Independent StudySkills practice12:002:00MCQ online quiz, compulsory to pass.
Scheduled Learning And Teaching ActivitiesSmall group teaching121:0012:00Tutorial sessions, Present-in-person
Guided Independent StudyIndependent study121:0012:00Online lectures
Guided Independent StudyIndependent study140:0040:00General revision, reviewing lecture notes, background reading
Guided Independent StudyIndependent study111:0011:00Examination revision
Total100:00
Teaching Rationale And Relationship

The lectures are designed to assist students in the acquisition of a knowledge base that will facilitate understanding of concepts, methods tools and techniques.

Independent study involves:
1.       study following lectures and practicals
2.       study in preparation for the assessed coursework and exams, which provides an opportunity to bring
together relevant knowledge and understanding and cognitive, research-related, and assessed key skills.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Other Assessment
Description Semester When Set Percentage Comment
Report2M100Open-book Report on statistics, taking approximately 11 hours.
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
Computer assessment2MMCQ online quiz, it is compulsory to pass it.
Assessment Rationale And Relationship

The report on statistics (semester 2) provides students with an opportunity to demonstrate knowledge, understanding and the possession of subject-specific, cognitive and key skills.

The research skills material covered in the module is assessed via the end of semester computer based MCQ examination.

Reading Lists

Timetable