TRANSFORMING HIGHER EDUCATION THROUGH EXCEPTIONAL ONLINE LEARNING

Authors

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Sandro Leidi:
Lead advisor and course author

A senior statistician at the Statistical Services Centre, University of Reading, Sandro has been working in Statistics since 1997, training professionals and providing training to institutions. Along with his colleagues, he has been delivering statistical e-learning since 2004. His consultancy group has many renowned clients, including the National Audit Office, UK, and the United Nations Framework Convention for Climate Change.

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Wilma Alexander:
Accessibility advisor

Wilma Alexander is part of the Learning Services team at the University of Edinburgh, supporting the use of online tools and technologies across the university. She has a special interest in usable and accessible digital practice, tutors on usability and accessibility for the university's Master's in Digital Education, and promotes the use of online activities for inclusive teaching and learning in the context of staff development.

Learning outcomes

By the end of this course you will be able to:

  • Assess how much you already know about Statistics
  • State what the Statistical Methods for Research programme covers
  • Explain how Statistics can contribute to your research project
  • Outline the stages of a modern statistical investigation
  • Recognise that there are two parts to a statistical model, written as Data = Pattern + Residual.

Course structure

The diagram on the right explains the chronology of the course. Click on each of the sections to view a more detailed breakdown of this course.

Orientation

Introduction to the course, helping you gain a feel for how it will develop.

Course files

The course content. The target knowledge and concepts are introduced during this stage.

Course quiz

A chance to test your knowledge and recall
what you have learned from the course so far.

Highlights

Course highlights include:

  • A pre-programme quiz which gives you the opportunity to gauge your existing knowledge. This quiz is then repeated in the final course, 'Conclusion: Putting your skills into practice', allowing you to measure your progress.
  • A cycle diagram activity taking you through the iterative stages of a statistical model.
  • Video interviews with experts explaining their research and how they approach study design.
  • A 'Statistics in the real world' pod linking to a broadcast that examines the use of statistics within the media and publicised reports.
  • A course quiz to test the concepts learned in this course.

Supporting institutions

The Statistical Methods for Research programme has been developed in conjunction with the following institutions:

  • Brunel University, UK
  • Dublin Institute of Technology, Ireland
  • Edith Cowan University, Australia
  • James Cook University, Australia
  • London Metropolitan University, UK
  • Sheffield Hallam University, UK
  • University College Cork, Ireland
  • University of Birmingham, UK
  • University of Brighton, UK
  • University of Huddersfield, UK
  • University of Reading, UK

Authors

Sandro Leidi: Lead advisor and course author

A senior statistician at the Statistical Services Centre, University of Reading, Sandro has been working in Statistics since 1997, training professionals and providing training to institutions. Along with his colleagues, he has been delivering statistical e-learning since 2004. His consultancy group has many renowned clients, including the National Audit Office, UK, and the United Nations Framework Convention for Climate Change.


Wilma Alexander: Accessibility advisor

Wilma Alexander is part of the Learning Services team at the University of Edinburgh, supporting the use of online tools and technologies across the university. She has a special interest in usable and accessible digital practice, tutors on usability and accessibility for the university's Master's in Digital Education, and promotes the use of online activities for inclusive teaching and learning in the context of staff development.


Learning outcomes

By the end of this course you will be able to:

  • Assess how much you already know about Statistics
  • State what the Statistical Methods for Research programme covers
  • Explain how Statistics can contribute to your research project
  • Outline the stages of a modern statistical investigation
  • Recognise that there are two parts to a statistical model,
    written as Data = Pattern + Residual.

Course structure

The bullet points below explain the chronology of the course and give a breakdown of each of the sections you will encounter.

Orientation

The Orientation section introduces you to the content and aims of the course. There is an opportunity to assess your current knowledge, to help you evaluate your learning at the end of the course.

  • Introduction

Course files

The course files contain the core course content. The content is divided into units and screens.

  • Unit 1: Getting started
  • Unit 2: Statistical investigation

Course quiz

The Course quiz section allows you to assess and consolidate what you have learned in the course.

  • Course quiz

Highlights

Course highlights include:

  • A pre-programme quiz which gives you the opportunity to gauge your existing knowledge. This quiz is then repeated in the final course, 'Conclusion: Putting your skills into practice', allowing you to measure your progress.
  • A cycle diagram activity taking you through the iterative stages of a statistical model.
  • Interviews with experts explaining their research and how they approach study design.
  • A 'Statistics in the real world' pod linking to a broadcast that examines the use of statistics within the media and publicised reports.
  • A course quiz to test the concepts learned in this course.

Supporting institutions

The Statistical Methods for Research programme has been developed
in conjunction with the following institutions:

  • Brunel University, UK
  • Dublin Institute of Technology, Ireland
  • Edith Cowan University, Australia
  • James Cook University, Australia
  • London Metropolitan University, UK
  • Sheffield Hallam University, UK
  • University College Cork, Ireland
  • University of Birmingham, UK
  • University of Brighton, UK
  • University of Huddersfield, UK
  • University of Reading, UK