Tutor: Dr Andrew Terhemen Tyowua

Preparing high-quality graphs for publication of scientific research papers using Microsoft Excel

Course cost: $11.50 (individuals); $499.50 (institutions)

Course duration: 1h: 20 min

Course description

Preparing high-quality graphs is the first critical step towards preparing a scientific research paper for publication. However, there is limited training on creating high-quality graphs for this purpose. Consequently, many researchers publish research papers with low-quality graphs that are difficult to read and understand, which reduces the impact of the findings. In some cases, competent reviewers suggest improvement of low-quality graphs before publication while in other cases, they reject the manuscript. Both cases delay the publication of the paper and reduce the productivity of the author(s).

High-quality graphs can be created with a wide range of different software including MATLAB, SCILAB, Python, Julia, Origin and Microsoft Excel once a researcher learns the fundamental principles underpinning data visualization in science. Microsoft Excel is a good place to start learning and practicing these principles because (i) it is readily available to users with Microsoft Office, (ii) does not require the knowledge of coding and (iii) can be quickly learnt. Therefore, this course is designed to enable learners gain practical skills on creating high-quality graphs in Microsoft Excel for scientific publications, which can be applied in other software for the same purpose.

The course covers types of graphs and their uses, differences between low- and high-quality graphs, strategies for creating high-quality graphs in Microsoft Excel, grouping and saving the graphs for publication. Therefore, after successful completion of the course, the learner will be able to readily select the type of graph to use for a given dataset and create high-quality graphs using Microsoft Excel for scientific publications. Additionally, the learner will be awarded a certificate, which can add value to their CV.

The course will benefit postgraduate/graduate students, postdocs and early-career researchers in physical sciences, engineering, biomedical sciences, and other related fields. For postgraduate/graduate students, the course will help them prepare high-quality graphs for their dissertations or thesis.