This Data Science jargon buster to help
Data Science jargon buster – for Data Scientists ..
Data Science Jargon For Beginners - Null Hypothesis & …
I always respected Dennis and Brian the most in the FE field, and I valued their integrity above all else. Their great hearts attracted me to them, not their talent, genius, or fame. I have written plenty about my days with and , and interested readers can discover more if they wish. I hope to convey what the learning experience of carrying their spears was like. My and comprised the kind of education that few survive for long. Although my education with Brian was far gentler, I learned important lessons from him. If not for my adventures, I would not have much worth saying. Even though much of this essay “merely” deals with mainstream science theory and data, . This essay is obviously not the work of a professional scientist, historian, or economist.
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One major problem with making a positive impact on a global level, ultra-elite machinations aside, is that almost nobody focuses on what is important, which I hope to help remedy with this essay. Almost everybody hacks at branches if they hack at all. Conspiracists tend to obsess on elite machinations, which is an exercise of dubious benefit to begin with, but they often become paranoid and also confuse retail elites or other interests with the GCs. Bill Gates and David Rockefeller are probably not members of the GCs’ organization. Also, I learned that ultra-elites can only play their games with the responsibility that almost all people have abdicated as they play the victim. The GCs are only a symptom of our malaise, not a cause. They cannot be beaten at their game, and it is counterproductive and can even be suicidal to try. Making them obsolete is probably the best that we can do. While conspiracists often fixate on ultra-elite machinations, intellectuals, academics, and scientists tend to deny that such activities even exist or are meaningful. It took me many years to understand their resistance to even acknowledging ultra-elite existence, and I think it partly relates to the mainstream scientific worldview that . They have an ideological aversion to the notion that anybody manipulates events on a global scale, and believe that what seems conspiratorial is only anarchic elites competing with each other, which is like Darwin’s view of evolution. They believe that conspiracists see a pattern where none exists, or that the situation can be explained without invoking conscious intent, like materialistic hypotheses of how the universe operates. Radical leftists have to the of such elites; such an idea scares them. Neither obsession nor denial helps people attain productive understandings of the issue. Conspiracists and structuralists are united in thinking like victims, and that, as I see it, . Until they relinquish thinking like a victim, they will not constructively engage the critical issues that humanity faces, and energy ranks above all else. Victims are reactive instead of proactive, and only and resulting action has a prayer of working, in my opinion.
Example of Bad Data Science: Test of Hypothesis
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But the branch of the that readers might find most interesting led to humans. Humans are in the phylum, and the last common ancestor that founded the Chordata phylum is still a mystery and understandably a source of controversy. Was our ancestor a ? A ? Peter Ward made the case, as have others for a long time, that it was the sea squirt, also called a tunicate, which in its larval stage resembles a fish. The nerve cord in most bilaterally symmetric animals runs below the belly, not above it, and a sea squirt that never grew up may have been our direct ancestor. Adult tunicates are also highly adapted to extracting oxygen from water, even too much so, with only about 10% of today’s available oxygen extracted in tunicate respiration. It may mean that tunicates adapted to low oxygen conditions early on. Ward’s respiration hypothesis, which makes the case that adapting to low oxygen conditions was an evolutionary spur for animals, will repeatedly reappear in this essay, as will . Ward’s hypothesis may be proven wrong or will not have the key influence that he attributes to it, but it also has plenty going for it. The idea that fluctuating oxygen levels impacted animal evolution has been gaining support in recent years, particularly in light of recent reconstructions of oxygen levels in the eon of complex life, called and , which have yielded broadly similar results, but their variances mean that much more work needs to be performed before on the can be done, if it ever can be. Ward’s basic hypotheses is that when oxygen levels are high, ecosystems are diverse and life is an easy proposition; when oxygen levels are low, animals adapted to high oxygen levels go extinct and the survivors are adapted to low oxygen with body plan changes, and their adaptations helped them dominate after the extinctions. The has a pretty wide range of potential error, particularly in the early years, and it also tracked atmospheric carbon dioxide levels. The challenges to the validity of a model based on data with such a wide range of error are understandable. But some broad trends are unmistakable, as it is with other models, some of which are generally declining carbon dioxide levels, some huge oxygen spikes, and the generally relationship between oxygen and carbon dioxide levels, which a geochemist would expect. The high carbon dioxide level during the Cambrian, of at least 4,000 PPM (the "RCO2" in the below graphic is a ratio of the calculated CO2 levels to today's levels), is what scientists think made the times so hot. (Permission: Peter Ward, June 2014)
Just as the aftermath of the appearance of complex life was uninteresting from a , as the amazingly diverse energy-generation strategies of archaea and bacteria were almost totally abandoned in favor of aerobic respiration, biological solutions to the problems that complex life presented were greatest during the Cambrian Explosion, and everything transpiring since then has been relatively insignificant. Animals would never see that level of innovation again. While investigating those eonic changes, many scientists have realized that the dynamics of those times might have been quite different from today’s, as once again may be of limited use for explaining what happened. Also, scientists generally use a rule-of-thumb called , or parsimony, which states that with all else being equal, simpler theories are preferred. , a seminal theorist regarding the scientific method, as they were easier to falsify. However, this issue presents many problems, and in recent times, theories of or speciation have invoked numerous interacting dynamics. Einstein noted that the more elegant and impressive the math used to support a theory, the less likely the theory depicted reality. Occam’s Razor has also become an unfortunate dogma in various circles, particularly , in which the of materialism and establishment science are defended, and often quite irrationally. Simplicity and complexity have been seesawing over the course of scientific history as fundamental principles. The recent trend toward multidisciplinary syntheses has been generally making hypotheses more complex and difficult to test, although and ever-increasing and more precise data makes the task more feasible than ever, at least situations in which are not interfering.
What are good ways to get started with data science for a ..
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Those processes and events can interact with each other, and a few examples can provide an idea of the dynamics’ complexity. What follows are today’s orthodox views, to the best of my knowledge, and they can certainly change in the future, perhaps even radically, just as cosmological and subatomic theories may change radically. It seems to me, however, that geophysical and geochemical processes are understood better and have more robust data than many other areas of science, so geophysics and geochemistry are areas where I expect fewer radical changes than others. Maybe that is because it is neither too big nor too small and closer to our daily reality than distant stars or what is happening inside atoms.
The greatest scientists readily admitted that the theories and data of physics, that hardest of the hard sciences, drew highly limited descriptions of reality, and those scientists were usually, to one extent or another, . If textbook science falls far short of explaining reality, what can be said within its framework that is useful? Plenty. Our industrialized world is based on textbook science and feats such as putting men on the Moon were performed within the parameters of textbook science. With the waning of overspecialization and overreliance on reductionism in the last decades of the 20th century, multidisciplinary works have proliferated and will tend to dominate the references for this essay. I have found them not only very helpful for my own understanding, but they are appropriate references for a generalist essay. I have also avoided scientific terminology when feasible. For example, I use “seafloor” instead of “,” and if a non-specialized term will suffice for a scientific concept, I will often use it.
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Guide to Data Science Cheat Sheets - KDnuggets
But to cut the marketing created jargon aside, a data scientist is ..
Data Scientist at Think ..
hypothesis is that the data scientist is ..
to becoming a data scientist;
Building data science teams - O'Reilly Radar
experiment and null-hypothesis of what a data scientist is were poorly designed to begin with
9/16/2011 · Building data science teams ..
4. If the results do not support your hypothesis, then explain why not; consider (1) problems with your understanding of the lab's scientific concept; (2) problems with your reasoning, and/or (3) problems with the laboratory procedure itself (if there are problems of reliability with the lab data or if you made any changes in the lab procedure, discuss these in detail, showing specifically how they could have affected the results and how the errors could have been eliminated).
The term that seemed to fit best was data scientist: ..
A frequent criticism in biology is that we don't publish our negative data. As a result, the literature has become biased towards papers that favor specific hypotheses (Nature, 422:554—5, 2003). Some scientists have become so concerned about this trend that they have created journals dedicated to publishing negative results (e.g., Journal of Negative Results in Biomedicine). Personally, I don't think they should bother.
The Difference Between Data Science and Data …
Chris Conlan began his career as an independent data scientist specializing in trading algorithms. He attended the University of Virginia where he …
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