Sign outside the public library at West Pittston, Pa., October 2016 https://www.futilitycloset.com/2025/06/22/noted-25/ #causality #coincidence #correlation

#TIL at work: sometimes, it may be okay to force a linear regression through the origin.

Normally speaking, you should use "y=ax+b" as model for your linear regressions and correlation indices. Because fixing "b=0" introduces a bias in the estimator "a".

However, today, someone argued that if you're using a regression to measure the predictive power of a model with respect to measurement data, you should fix "b=0".

Now, intuitively this makes some sense, but I haven't been able to find clear proof pro or against it.

So, if you know more about this *and* have relevant references to papers to backup your claim, I'd very much love to hear from you. Statistics is not really my field.

#correlation #regression #stats #statistics #math #maths

https://www.europesays.com/2156946/ CPI doesn’t propel markets #business #Correlation #CPI #equities #markets #TechnicalAnalysis

#correlation ≠ #causation

For the past year, stock and bond prices have mostly ebbed and flowed in tandem. Such positive #correlation has long been a big fear for many, as it reduces the benefit of holding both asset types. But what we just saw is a switch back, chart @ReutersMikeD https://www.reuters.com/markets/us/markets-may-be-waving-not-drowning-mike-dolan-2024-08-09/

LabPlot - A free OriginPro alternative for #Researchers (Scatter Plots)

@labplot@lemmy.kde.social

Catalyst Nanomaterials Lab has published another video tutorial that shows how to create stunning scatter plots, analyze correlations, and uncover hidden patterns in your data using #LabPlot. Go check it out!

https://www.youtube.com/watch?v=r1Fv1lAEf2c

Carl Sagan's guidelines to practice science

Thinking tools -
The Baloney Detection Kit: How to Think Sceptically and Bust Bullshit

https://themindcollection.com/baloney-detection-kit/

#science #philosophyofscience @philosophy @philosophyofmind @philosophie @science@newsmast.community @science@beehaw.org @science@lemmy.ml @science@lemmy.world @science@kbin.social @Scientits #thinking #criticalthinking #philosophy #astronomy #sagan #carlsagan #thinking #thinkingtools #authority #experts #fallacy #scepticism #correlation #stoicism #epistemology #research #researchmethodology

In 15 studies independently of BMI, women with #PCOS had higher #BPA levels. Carbohydrate #metabolism disorders were evaluated in 12 studies and in 6 a positive correlation was found with BPA levels. "Bisphenol A and polycystic ovary syndrome in human: A systematic review" #BisphenolA #correlation https://obgyn.onlinelibrary.wiley.com/doi/10.1002/ijgo.15349#:~:text=BPA%20level%20was%20related%20to,was%20found%20with%20BPA%20levels.

What do you do when you encounter a weird thing in your research? Blog about it!

Inspired by today's sleuthing about weird looking correlation histograms, here is a post actually digging into it at least a little bit (there's probably way deeper one could go, but this was good enough for me).

Weird Correlation Patterns
https://rmflight.github.io/posts/2024-04-03-weird-correlation-patterns/

Original post was: https://mastodon.social/@rmflight/112208708775047549

#RStats #statistics #correlation help?!

I've got a bunch (3.5 x 10^6) gene-gene _Kendall-tau_ correlations, where each correlation is based on 12 samples. When I visualize the histogram of correlations, with a default of 30 bins, I see pic #1. Which looks fine, personally.

When I go to my personal favorite number of bins, 100, I get pic #2, with weird lows below the peaks.

Is this just me being paranoid as to something weird causing the alternating high and low values?

edit to add cor type

Very happy that our review paper "A primer on #correlation-based #dimension #reduction methods for #multi-omics analysis" is out. Thanks to the reviewers & journal too for their help.

https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0344

#genomics #omics #systems #data #model #modelling #biology #transcriptomics

In the early 2000s, #SvenHenkel and myself developed an #IDMEF/ #IDXP compliant security event message pipelining framework for collecting and consolidating log messages, e.g., from network #IDS, and #EDR products.

In the messages stream, we were able to match multi-stage #correlation #DetectionRules in near real-time (in-memory), before everything was stored in a central database. Structural graph-based #AnomalyDetection was developed later by some colleagues.

We called it #MetaIDS.