Reading the news seems a lot like doom and gloom these days, what with the threat of nuclear war always on the headlines. The devastation that nuclear reactions can achieve is undeniable; however their effects reach far beyond the immediate blast damage and thermal radiation that can be observed. Another danger lurks – unseen and undetected – but nonetheless capable of widespread destruction.
Spectroscopy is not only an important part of a scientist’s arsenal, but also a big part of everyday life. Take a moment to appreciate that the myriads of colours in dyes and paints are made possible by chemical compounds that possess certain spectral characteristics, or how the chemical composition of distant galaxies can be characterised based on their observed spectra. In this tutorial we will be discussing how infrared spectroscopy works, and its applications.
Merry Christmas! As we relax and unwind this holiday season, look out the window and observe the falling of snowflakes (if you’re fortunate enough to be able to!). Each icy crystal begins its existence high up in the atmosphere and slowly alters its appearance as it falls but always retaining its hexagonal structure, nature ever the master craftsman… Continue reading
As I approached the completion of my undergraduate degree, I was definitely unsure of how research worked and the expectations that were required of me going forward. This resulted in a bit of confusion as I learned the ropes and how to handle my newfound freedom as I set out to do some proper research.
Looking back, I think what would have benefited me greatly was some simple guidance as I transitioned from routine, scheduled lectures to the erratic and unpredictable world of research. Guidance such as this feature article co-written with a fantastic collaborator.
One thing that regularly stumps scientists is the handling of data. We seem to be very good at generating obscene amounts of it, but representing it meaningfully can be a little off putting if you don’t happen to be a bioinformatician. In previous tutorials we looked at hypothesis testing using variations of the t-Test, and we continue the series by comparing more than 2 samples sets with ANOVA.
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What is with these things!?
One thing that regularly stumps scientists is the handling of data. We seem to be very good at generating obscene amounts of it, but representing it meaningfully can be a little off putting if you don’t happen to be a bioinformatician. Let’s continue our tutorial series by introducing Two-Sample t-Tests and Paired t-Tests to see how we can easily incorporate statistical analysis into our work.