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Ishikawa diagrams (also called fishbone diagrams, [ 1] herringbone diagrams, cause-and-effect diagrams) are causal diagrams created by Kaoru Ishikawa that show the potential causes of a specific event. [ 2] Common uses of the Ishikawa diagram are product design and quality defect prevention to identify potential factors causing an overall effect.
Five whys (or 5 whys) is an iterative interrogative technique used to explore the cause-and-effect relationships underlying a particular problem. [1] The primary goal of the technique is to determine the root cause of a defect or problem by repeating the question "why?" five times, each time directing the current "why" to the answer of the ...
The four causes or four explanations are, in Aristotelian thought, four fundamental types of answer to the question "why?" in analysis of change or movement in nature: the material, the formal, the efficient, and the final. Aristotle wrote that "we do not have knowledge of a thing until we have grasped its why, that is to say, its cause."
Causality. Causality is an influence by which one event, process, state, or object ( a cause) contributes to the production of another event, process, state, or object (an effect) where the cause is at least partly responsible for the effect, and the effect is at least partly dependent on the cause. In general, a process can have multiple ...
Causal reasoning is the process of identifying causality: the relationship between a cause and its effect. The study of causality extends from ancient philosophy to contemporary neuropsychology; assumptions about the nature of causality may be shown to be functions of a previous event preceding a later one. The first known protoscientific study ...
[2] Impact evaluations seek to answer cause-and-effect questions. In other words, they look for the changes in outcome that are directly attributable to a program. [3] Impact evaluation helps people answer key questions for evidence-based policy making: what works, what doesn't, where, why and for how much?
Climate change - Wikipedia is an article that explains the causes, effects, and responses to the global phenomenon of climate change. Learn about the science, history, and politics of this urgent issue.
Causal inference is the process of determining the independent, actual effect of a particular phenomenon that is a component of a larger system. The main difference between causal inference and inference of association is that causal inference analyzes the response of an effect variable when a cause of the effect variable is changed. [ 1][ 2 ...