31. Data analysis basics and how to make the most of the collected data

Science on surfaces - Tips, Tricks and Tools

Data analysis basics and how to make the most of the collected data

How do you maximize the information extraction from that data that you may have spent weeks collecting? And what is the difference between ‘precision’ and ‘accuracy’?

In this episode, we talk to Prof. Marina Axelson-Fisk, Professor in Mathematical Statistics at Chalmers University of Technology about Data analysis, to learn more about how to make the most of the data that you have collected.

In this informative conversation, Prof. Axelson-Fisk guides us through a range of different data analysis types such as exploratory-, descriptive-, and predictive analysis and explains when to use which method. We also talk about the data analysis process from start to end; how to handle the data before you analyze it, requirements on the data input, and how to assess the analysis output. We then move on to briefly discuss data modelling and key aspect related to this procedure. Prof Axelson-Fisk’s explains key terminology such as repeatability, replicability and reproducibility. And, finally and once and for all, we get the difference between precision and accuracy explained. Last but not least, we talk about the main challenges with data analysis, what pitfalls to look out for, and we get a recommendation on data analysis software to use.

By the way, the English translation of ‘supraledare’ is of course ‘superconductor’

Thanks for listening! If you are interested in surface and interface science and related topics, you should check out our blog - the Surface Science blog