As data-driven professionals, understanding the "cumulative mean" can revolutionize our statistical analysis. 📈 This insightful measure unveils the evolving average value of a dataset over time, making it perfect for time-series analysis, trend spotting, and smoothing noisy data.
Hey fellow data enthusiasts! 📊 In this post, I want to share an exciting technique called rolling correlation and how you can leverage it to gain valuable insights from your time-series data using R.
Don't be shy—give it a try and share your findings in the comments below.
Morning mood: the CNN situation makes it pretty clear that as Canadians, we're going to have to think about what it is going to be like living next to a brutal dictatorship with the disappearance of the rule of law, complete compromise of the courts, and probably mass executions, prison camps, and a flood of refugees coming to our border. It seems inevitable that this is where America is headed. We are witnessing the death of democracy in real-time. The media is once again going to aid and abet it's destruction in a race for ratings
As you might guess, I'm in a pretty pissy mood this morning.
@jimcarroll@aadmaa I share the general sentiment of your fine mornings' rant, as well as your concern that some worst-case outcomes are absolutely possible. But I do think positive outcomes are also possible, and even more likely than the negative. I think ,y sense of US politics is a bit different from yours - and in particular I don't buy that a black swan event is needed to to bring America back from the Trump era.
I believe we can draw an analogy to time series analysis of ECG or EEG data. When you are about to have certain types of cardiac events or seizures, the dimensionality of the space drops. The can signal loses its complexity and become very simple, like going from an orchestral concert to the simplicity of a dull, regular drum beat. THUD THUD THUD THUD... And then, cue the cardiac event/seizure.
The dimensionality of the space of US political discourse can be measured as a behavior. (See e.g. https://www.pnas.org/doi/10.1073/pnas.2205791119 - check out "A General Definition of Dimensionality in Behavior") You'd see that the dimensionality has collapsed - i.e., the number of functions of past behavior needed to predict future behavior becomes very low. Because you can predict way too much knowing way too little.
In this sense exactly, I believe what's been happening in US politics is analogous to a seizure or a heart attack: the orchestral complexity has collapsed into a dull THUD, THUD of very low dimension. And while a seizure can kill us, can hurt us, it's quite likely that we survive, and that after it passes as a seizure does, complexity of thought will reemerge naturally. Because we are many thoughtful, creative, independent/dependent/interdependent minds after all.