1. KNOWLEDGE AND UNDERSTANDING: to understand the different types of graphs and for which kinds of datasets each one is more or less appropriate. To understand the message conveyed by graphs and images. To understand the importance of authors' copyrights.
2. APPLYING KNOWLEDGE AND UNDERSTANDING:
To learn how to manage experimental data and use the most appropriate charts to graph them. To learn how to read graphs. To learn the basics of Excel to represent own data in appropriate and informative graphs. To learn the key features of attractive and informative images for scientific works. To learn how to ask for copyright permission and indicate it in figure legends.
3. MAKING JUDGEMENTS: to learn how to assess and evaluate critically graphs and images to understand whether their representation is objective and complete or partial.
4. COMMUNICATION SKILLS: to learn to make graphs and images that communicate a correct, complete and objective message.
5. LEARNING SKILLS: to learn where to find tutorials and software tools to build and edit graphs in software such as Excel. To understand where to find key parameters that define images (e.g., resolution and colour palette).

nessuno

The first module will teach the importance and how to represent data with appropriate graphs and the importance and types of clear and informative images in scientific works. Copyrights and softwares for images and graphs. Discussion of examples.

"Graphing Statistics & Data: Creating Better Charts" by Anders Wallgren, Britt Wallgren, Rolf Persson, Ulf Jorner, Jan-Aage Haaland. Sage Publications. 1996. London, UK.

The first module will teach the importance to represent (experimental) data with appropriate graphs and the importance of having clear and informative images in scientific works (articles, thesis, reports, etc.). Importance of the quality and quantity of data and information to convey in an image or graph. Types of images (photos, schemes, diagrams), type of formats (tiff, jpg, png, etc.) and their salient features (resolution, colour palettes, background, etc.). Image copyrights and correct use thereof. Examples of software to build and edit images. Key aspects of Chemdraw to build chemical structures. Graph types (e.g., lines, scatter, histograms, bars, radar, etc.). How to choose the best graph to represent experimental data. Key elements to prepare correctly a graph: axes, colours, legends, font types, line width, error bars, etc. Key elements to evaluate critically graphs and their content. Basic principles of Excel to graph data: sheets, columns, raws, type of content (number, text, etc.), key commands, basic formulas, shortcuts for commands. Examples of graphs that are incorrect, unreadable and not objective. Examples of clear and correct graphs.

Interactive methods (Moodle 2). Slides.

Any changes to the methods described here, which may be necessary to guarantee the application of safety protocols related to any emergency situations, will be communicated on the Department website, the Course of Study website and on the teaching Moodle page.

Preparation of a brief report (max. 2 pages) with data representation. The evaluation will be of approval if the student demonstrates to understand what is taught and to be able to apply it.