Christmas came early for the https://t.co/hROOViBy3F! This should replace our two old MiSeqs and provide higher quality reads (for the full 2x300bp) and double our average number of reads per sample for the same price. Thanks to Andre Comeau, IMR Manager, for the photo op.
Understanding the difference between Standard Deviation (SD) and Standard Error (SE) is crucial for accurate data interpretation. SD measures the variability within your data, indicating how spread out the individual data points are from the mean.
In contrast, SE measures the uncertainty around the sample mean as an estimate of the population mean. It reflects the precision of the mean, with SE decreasing as the sample size increases, making your estimate more reliable.
The relationship between SD and SE is given by the formula: SE = SD / √(sample size). While SD remains relatively constant with larger samples, SE diminishes, highlighting the reduced uncertainty in the mean estimate.
A common mistake in research is using the “±” notation without specifying whether it refers to SD or SE, leading to potential misinterpretation of the data. Clear distinction is essential for transparency and accuracy in reporting.
Key Takeaways:
• Use SD to describe data variability.
• Use SE to indicate the precision of the mean.
• Always specify which measure you are reporting.
Advanced #Microbiome Analysis, class of 2024! We had participants from across Canada and as far as Mexico and Kazakhstan. As always, our materials are open-access... 🧵
My MSc student @benfish404 decided to dress up as me today for Halloween! I wasn't in the office today, so he took the opportunity to take over my office and have a photo shoot, lol
Is there a one-size-fits all best taxonomic classifier for metagenomes? Read about it in our paper, out now in @MicrobioSoc#MGen!
https://t.co/bg8Uo0gCIJ
And scroll on for a short audio or video summary of our key findings!
@BetaScience@ICG_Dalhousie
Neural mapping, parasitic plant genomes, and sleeping hydras - this is a great watch on 2021's breakthroughs in neuroscience and biology!
https://t.co/esdETxaRxc