"Nature is capable of building complex structures by processes of self-organization; simplicity begets complexity." (Victor J Stenger, "God: The Failed Hypothesis", 2010)
"[…] a conceptual model is a diagram connecting variables and constructs based on theory and logic that displays the hypotheses to be tested." (Mary W Celsi et al, "Essentials of Business Research Methods", 2011)
"The justification for naturalism is that it works: we have never understood anything about the universe by assuming the supernatural, while assuming naturalism as a working hypothesis has moved our understanding ever forward." (Jerry Coyne, "Is atheism irrational? A philosopher says yes", 2014)
"Observation and experiment, without a rational hypothesis, is like a man groping at objects at random with his eyes shut." (Henry P Tappan, "Elements of Logic", 2015)
"Various scientific methodologies are themselves mental models through which scientists discover, predict, and hypothesize about what we then call reality. In the social constructionist paradigm such mental models frame all our experiences. They schematize, and otherwise facilitate and guide the ways in which we recognize, react, and organize the world. How we define the world is dependent on such schema and thus all realities are socially structured. In the socially constructed paradigm, the multivariate mental models or conceptual schema are the means and mode through which we constitute our experiences." (Patricia H Werhane et al, "Obstacles to Ethical: Decision-Making Mental Models, Milgram and the Problem of Obedience", 2013)
"Science, at its core, is simply a method of practical logic that tests hypotheses against experience. Scientism, by contrast, is the worldview and value system that insists that the questions the scientific method can answer are the most important questions human beings can ask, and that the picture of the world yielded by science is a better approximation to reality than any other." (John M Greer, "After Progress: Reason and Religion at the End of the Industrial Age", 2015)
"We are superb causal-hypothesis generators. Given an effect, we are rarely at a loss for an explanation. Seeing a difference in observations over time, we readily come up with a causal interpretation. Much of the time, no causality at all is going on—just random variation. The compulsion to explain is particularly strong when we habitually see that one event typically occurs in conjunction with another event. Seeing such a correlation almost automatically provokes a causal explanation. It’s tremendously useful to be on our toes looking for causal relationships that explain our world. But there are two problems: (1) The explanations come too easily. If we recognized how facile our causal hypotheses were, we’d place less confidence in them. (2) Much of the time, no causal interpretation at all is appropriate and wouldn’t even be made if we had a better understanding of randomness." (Richard E Nisbett, "Mindware: Tools for Smart Thinking", 2015)
"We don’t recognize how easy it is to generate hypotheses about the world. If we did, we’d generate fewer of them, or at least hold them more tentatively. We sprout causal theories in abundance when we learn of a correlation, and we readily find causal explanations for the failure of the world to confirm our hypotheses. We don’t realize how easy it is for us to explain away evidence that would seem on the surface to contradict our hypotheses. And we fail to generate tests of a hypothesis that could falsify the hypothesis if in fact the hypothesis is wrong. This is one type of confirmation bias." (Richard E Nisbett, "Mindware: Tools for Smart Thinking", 2015)
"In terms of characteristics, a data scientist has an inquisitive mind and is prepared to explore and ask questions, examine assumptions and analyse processes, test hypotheses and try out solutions and, based on evidence, communicate informed conclusions, recommendations and caveats to stakeholders and decision makers." (Jesús Rogel-Salazar, "Data Science and Analytics with Python", 2017)
"It is in fact mathematics itself that is simplest in hypothesis and also richest in phenomena (i.e. the simple source of all complexity). In ontological mathematics, all of existence comprises sinusoidal waves arranged into autonomous units called monads, and these are all that are required to explain everything." (Thomas Stark, "God Is Mathematics: The Proofs of the Eternal Existence of Mathematics", 2018)
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