Causality

Causality Definition: It denotes a necessary relationship between one event (called cause) and another event (called effect) which is the direct consequence (result) of the first event. OR A relationship between one event or action that precedes and initiates a second action or influences the direction, nature, or force of a second action. In scientific study, causality must be observable, predictable, and reproducible and thus is difficult to prove.

While this informal understanding will sayisfy in everyday use, the philosophical analysis of causality has proven difficult. When we discuss about western philosophical tradition our mind goes back at least as far as Aristotle, and the topic brought contemporary philosophy journals closer together,it means by the practice of this topic all the journals came together. Though cause and effect are typically related to events, yet processes, properties, variables, facts, and states of affairs has as yet no universally accepted answer, and remains under discussion. According to Sowa (2000), up until the twentieth century, three assumptions described by Max Born in 1949 were dominant in the definition of causality: 1. "Causality postulates that there are laws by which the occurrence of an entity B of a certain class depends on the occurrence of an entity A of another class, where the word entity means any physical object, phenomenon, situation, or event. A is called the cause, B the effect.

2. "Antecedence postulates that the cause must be prior to, or at least simultaneous with, the effect. 3. "Contiguity postulates that cause and effect must be in spatial contact or connected by a chain of intermediate things in contact."

Physics Physicists conclude that certain elemental forces: gravity, the strong and weak nuclear forces, and electromagnetism are said to be the four fundamental forces which are the causes of all other events in the universe. Causality is hard to explain to ordinary language from many different physical theories. One problem is typified by the moon's gravity. Its not accurate to say, "the moon exerts (try) a gravitic pull and then the tides rise." In Newtonian mechanics gravity, rather, is a law expressing a constant observable relationship among masses, and the movement of the tides is an example of that Relationship. There are no discrete (Separate) events or "pulls" that can be said to proceed the rising of tides. Explaining the gravity causally is even more complicated in general relativity. Another important implication of Causality in physics is its closely connection to the Second Law of Thermodynamics . Quantum mechanics is yet another branch of physics in which the nature of causality is somewhat unclear. The treatment of the concept of causality within the Second Law of Thermodynamics yields a loss in the translation. The statistical basis of the maintenance of the exchange of entropy keep the subject to an extent such that the observer loses perspective. The 2nd Law states that "in an isolated system, entropy cannot decrease". This is a corollary of the concept that an effect cannot be greater than the cause.

Engineering (Causal System) A causal system (also known as a physical or nonanticipative system) is a system where the output y(t) at some specific instant t0 only depends on the input x(t) for values of t less than or equal to t0. Therefore these kinds of systems have outputs and internal states that depend only on the current and previous input values. The idea that the output of a function at any time depends only on past and present values of input is defined by the property commonly referred to as causality. A system that has some dependence on input values from the future (in addition to possible dependence on past or current input values) is termed a non-causal or acausal system, and a system that depends solely on future input values is an anticausal system. Note that some authors have defined an anticausal system as one that depends solely on future and present input values or, more simply, as a system that does not depend on past input values.

Classically, nature or physical reality has been considered to be a causal system. Physics involving special relativity or general relativity require more careful definitions of causality, as described in causality (physics). The causality of systems also plays an important role in processing, in signal processing, a causal filter is a linear and time-invariant causal system. The word causal indicates that the filter output depends only on past and present inputs. A filter whose output also depends on future inputs is acausal. A filter whose output depends only on future inputs is anti-causal. Systems (including filters) that are realizable (i.e. that operate in real time) must be causal because such systems cannot act on a future input. In effect that means the output sample that best represents the input at time comes out slightly later. A common design practice is to create a realizable filter by shortening and/or time-shifting a noncausal impulse response. If shortening is necessary, it is often accomplished as the product of the impulse-response with a window function.

Causality contrasted with conditionals Conditional statements are not statements of causality. An important distinction is that statements of causality require the antecedent to precede the consequent in time, whereas conditional statements do not require this temporal order. Confusion commonly arises since many different statements in English may be presented using "If ..., then ..." form

(and, arguably, because this form is far more commonly used to make a statement of causality). The two types of statements are distinct, however. For example, all of the following statements are true when Explain” If ..., then ..." as the material conditional: •

If George Bush is president of the United States in 2004, then Germany is in Europe.

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If George Washington is president of the United States in 2004, then Germany is in Europe.

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If George Washington is president of the United States in 2004, then Germany is not in Europe.

The first is true since both the antecedent and the consequent are true. The second is true because the antecedent is false and the consequent is true. The third is true because both the antecedent and the consequent are false. These statements are trivial examples. Of course, although none of these statements expresses a causal connection between the antecedent and consequent, they are nonetheless all true because no statement has the combination of a true antecedent and false consequent. Logic requires only that truth not be deceptive. The ordinary indicative conditional has somewhat more structure than the material conditional. For instance, although the first is the closest, none of the preceding three statements seems true as an ordinary indicative reading. But the sentence •

If Shakespeare of Stratford-on-Avon did not write Macbeth, then someone else did.

intuitively seems to be true, even though there is no straightforward causal relation in this hypothetical situation between Shakespeare's not writing Macbeth and someone else's actually writing it. Another sort of conditional, the counterfactual conditional, has a stronger connection with causality, yet even counterfactual statements are not all examples of causality. Consider the following two statements: 1. If A were a triangle, then A would have three sides. 2. If switch S were thrown, then bulb B would light. In the first case, it would not be correct to say that A's being a triangle caused it to have three sides, since the relationship between triangularity and three-sidedness is that of definition. The property of having three sides actually determines A's state as a triangle. Nonetheless, even when interpreted counterfactually, the first statement is true.

A full grasp of the concept of conditionals is important to understanding the literature on causality. A crucial stumbling block is that conditionals in everyday English are usually loosely used to describe a general situation. For example, "If I drop my coffee, then my

shoe gets wet" relates an infinite number of possible events. It is shorthand for "For any fact that would count as 'dropping my coffee', some fact that counts as 'my shoe gets wet' will be true". This general statement will be strictly false if there is any circumstance where I drop my coffee and my shoe doesn't get wet. However, an "If..., then..." statement in logic typically relates two specific events or facts -- a specific coffee-dropping did or did not occur, and a specific shoe-wetting did or did not follow. Thus, with explicit events in mind, if I drop my coffee and wet my shoe, then it is true that "If I dropped my coffee, then I wet my shoe", regardless of the fact that yesterday I dropped a coffee in the trash for the opposite effect --the conditional relates to specific facts. More counterintuitively, if I didn't drop my coffee at all, then it is also true that "If I drop my coffee then I wet my shoe", or "Dropping my coffee implies I wet my shoe", regardless of whether I wet my shoe or not by any means. This usage would not be counterintuitive if it were not for the everyday usage. Briefly, "If X then Y" is equivalent to the first-order logic statement "A implies B" or "not B-and-not-A", where A and B are predicates, but the more familiar usage of an "if A then B" statement would need to be written symbolically using a higher order logic using quantifiers ("for all" and "there exists").

Causality Loop •

A temporal causality loop, or predestination paradox, is a theoretical phenomenon, which is said to occur when a chain of cause-effect events is circular. For instance, if event A causes event B, and event B causes event C, and event C causes event A, then these events are said to be in a causality loop.

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A causality loop diagram (also known as a causal loop diagram) is a scientific diagram for showing the influence of two interrelated variables.

The concept of a causality loop is functionality comparable to those of positive feedback, coproduction (social science), and co-evolution, all of which describe how two or more variables of a system affect each other and therefore create each other, albeit with respect to different variables operating at different scales. Co-production is concerned with the variables of science/technology and society operating at the scale of society. Co-evolution is concerned with the variables of species operating at the scale of the evolutionary process. Causality loops and positive feedback are more abstract, and theoretically applicable to any set of variables operating at any scale. Co-production, causality loops, and positive feedback are also related to the concept of virtuous circle and vicious circle – when the co-production, causality loop, or positive feedback produces a desirable effect, systems change is described as a virtuous circle; when they produce an undesirable effect, systems change is described as a vicious circle. Because these concepts refer to variables interacting in a complex system, they all produce unintended consequences – virtuous cycles produce unintended benefits and vicious cycles produce unintended harms. Although such consequences are unintended in the sense that no actor deliberately intends for them to occur, unintended consequences

are an expected emergent property of systems change (in accordance with the ways Langdon Winner proposes that artifacts can ‘have politics’), and can be used as an indicator of systems change. Taking examples from the field of environmental justice, although community empowerment was an unintended benefit of a bucket brigade (which were originally intended as a practical air sampling device), they are an indicator of systems change. On the flipside, although environmental injustices may be unintentional, they are an expected consequence of inequality in our socio-economic system. Although these various concepts have significant differences, a result of the disciplines from which they emerged and the topics to which they’re applied, they are functionally comparable in that they satisfy a similar conceptual function of describing dynamic and generative interaction between two or more variables in a system.

Perdication As 2nd definition Report 17july2005 The wars in Iraq and Afghanistan have already cost taxpayers $314 billion, and the Congressional Budget Office projects additional expenses of perhaps $450 billion over the next 10 years. Especially, The war of Iraq it costs so much then it was expected so, it affected the U.S economy badly. The Center for Strategic and Budgetary Assessments, a nonpartisan Washington think tank, has estimated that the Korean War cost about $430 billion and the Vietnam War cost about $600 billion, in current dollars. According to the latest estimates, the cost of the war in Iraq could exceed $700 billion. Put simply, critics say, the war is not making the United States safer and is harming U.S. taxpayers by saddling them with an enormous debt burden, since the war is being financed with deficit spending. Some conservative experts outside Congress also have started questioning whether the war and its uncertain conclusion are worth the cost, in money and blood. "The objective has always been to install a friendly government," said Charles V. Peña, director of defense policy studies at the Cato Institute in Washington, a libertarian think

tank. "Are the costs worth that? No, because it's not something we can accomplish for the long term. It's just going to continue to drain the American taxpayer. I don't see how it's going to get better. It's only going to get worse." James Jay Carafano, a senior fellow for national security and homeland security at the Heritage Foundation, which supports the president on most matters, warned that the war's costs would only rise because of the growing need to repair and replace battered military equipment, from helicopters to Humvees. In addition, the rising death toll is making it harder for the military to recruit new soldiers, and long deployments are hurting the morale of National Guard and reserve units sent to Iraq. If the White House does not increase military spending, Carafano warned, the United States could end up with both a looming disaster in Iraq and a weaker military. "I don't think we're going to have enough money to run this military based on what they're asking for," said Carafano. "If you don't increase spending, you can hollow out the military."

He added that the war itself increasingly looks like a bad investment: "I think there is a point of diminishing returns in Iraq. There is a point where you're just throwing money at the problem. Quite frankly, I think we're at the tipping point." According to an analysis by the Democratic staff of the House Budget Committee, from the beginning of the war in March, 2003, through the fiscal year that ends Sept. 30, the

Bush administration has received a total of $314 billion in special appropriations for the wars. Just for the current fiscal year, the administration has received $107 billion in special appropriations, about $87 billion of which is directly related to military operations, according to the Center for Strategic and Budgetary Assessments. Most of the remainder has been spent on training and equipping Iraqi forces. U.S. taxpayers must also cover other costs. For instance, the United States is spending $658 million to construct an embassy in Baghdad, which, with initial operating costs, could bring the expense of this super-secure facility to nearly $1.3 billion by the time it opens in several years. "Two years ago, no one expected the war would take this long," said Steven Kosiak, director of budget studies at the Center for Strategic and Budgetary Assessments. "On a per-troop basis, this war has been far more costly than expected, almost double the estimates.

My Points Causality is relation between the cause and effect, every cause is effect and every effect is cause. Loop of cause and effect is called Causality It means cause of any event (effect) become cause to an other event (effect). Example:

Economic policy of Pakistan Today Pakistan taken the load from an other rich countries (effect), this cause of poor policy economic in previous See the diagram observed it

P.E policy

Loan Poverity

Un Employment

Misuse of loan Poor investment

Boundaries or Condition

Crime

Uncertainty Condition