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Module

NES8008 : Data Analysis and Modelling (Inactive)

  • Inactive for Year: 2021/22
  • Module Leader(s): Dr Mark Shirley
  • Lecturer: Dr Aileen Mill, Professor Stephen Rushton, Dr Roy Sanderson
  • Owning School: Natural and Environmental Sciences
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 10
ECTS Credits: 5.0

Aims

The aim of this course is to deepen and expand the student's existing (undergraduate level) statistical knowledge to cover the principles of data analysis from recording/reporting and storage through exploration and visualisation to modelling.

It will develop the students' skills and understanding of current techniques of data science: exploring, wrangling, programming, modelling, and communicating the output of data sets. The students will become competent and confident in the methodologies involved and the value that they bring.

Introduce students to more advanced methods for natural and environmental systems.
Evaluation of models for management applications. Interpretation of output for policy and quantifying
uncertainty.

Outline Of Syllabus

Computational course with hands on learning of data analysis skills. Largely taught in a computer
Cluster based workshops using a mix of seminars and practicals to provide learning through worked examples.

The statistics and data handling will cover the broad range of applications and include introductions to multivariate and spatial statistics. Students are introduced to different approaches and applications throughout the course.

The modelling will consist of four components:

i) Techniques to explore, wrangle, and visualise data in a 'tidy' framework. Introduction to description and inference using statistics

ii) generalised linear models

iii) multivariate analysis

iii) problem-solving using a dynamic modelling approach. This aims to discuss how one would
create a model and use it to solve a real ecological problem

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion41:004:00Computer-delivered test on each of the 4 areas
Guided Independent StudyAssessment preparation and completion15:005:00Follow up to workshops – working on completion of numerical exercises
Guided Independent StudyAssessment preparation and completion115:0015:008 page report (12 pt Times Roman single space, approx. 2000 words with plots and tables)
Guided Independent StudyDirected research and reading110:0010:00Advance revision of basic statistics.
Scheduled Learning And Teaching ActivitiesWorkshops103:0030:00Data handling,descriptive statistics, multivariate analysis, generalised line & simulation modelling
Scheduled Learning And Teaching ActivitiesWorkshops13:003:00Evidence for Policy/ communicating uncertainty (GS)
Guided Independent StudyIndependent study110:0010:00Reading
Guided Independent StudyIndependent study123:0023:00running modelling generating results for analysis
Total100:00
Teaching Rationale And Relationship

Workshops to cover statistics application, working through problem solving exercises in groups and provide the hands-on training experience to enable students to develop a model of their own from first principles.

Teaching explains the challenging conceptual framework which underpins different modelling approaches in natural systems, backed up by references to the research literature.

Student-led problem-solving leads to independent study.

Assessment Methods

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

Other Assessment
Description Semester When Set Percentage Comment
Report1M1008 Page Report. approx. 2000 words
Assessment Rationale And Relationship

This report will take the form of an 8 page report. This will more readily demonstrate the teaching and learning objectives of the course, which is to learn how to analyse and problem-solve biological and ecological data.

Reading Lists

Timetable