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Causal research must be designed in such a way that the evidence regarding causality is clear. The main sources of data for causal research are interrogating respondents through surveys and conducting experiments

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Causal research must be designed in such a way that the evidence regarding causality is clear. The main sources of data for causal research are interrogating respondents through surveys and conducting experiments

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A causal inference may not be supported by known facts, but can often be correctly assumed.

Right after I saw lightning outside, our electricity went out. (causal: lightning caused the outage)


While it was raining very hard, I noticed the window was leaking water. (causal; rainwater found a break around the window)


After mom's car hit the pothole, the tire blew. (causal: the sharp edge of the pothole caused the tire to blow)

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A causal inference may not be supported by known facts, but can often be correctly assumed.

Right after I saw lightning outside, our electricity went out. (causal: lightning caused the outage)


While it was raining very hard, I noticed the window was leaking water. (causal; rainwater found a break around the window)


After mom's car hit the pothole, the tire blew. (causal: the sharp edge of the pothole caused the tire to blow)

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Hubert M. Blalock has written:

'Theory construction'

'Causal inferences in nonexperimental research'

'Causal inference in nonexperimental research'

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My source Avi Sion explains:

Causality refers to causal relations, i.e. the relations between causes and effects. This generic term has various, more specific meanings. It may refer to Causation, which is deterministic causality; or to Volition, which is (roughly put) indeterministic causality; or to Influence, which concerns the interactions between causation and volition or between different volitions.

The term 'causality' may also be used to refer to causal issues: i.e. to negative as well as positive answers to the question "are these things causally related?" In the latter sense, negations of causality (in the positive sense) are also causality (in the broad sense). This allows us to consider the Spontaneity (i.e. causelessness, the lack of any causation or volition) as among the 'causal' explanations of things.

A study of the field of causality must also include an investigation of non-causality in all its forms. For, as we shall see, even if we were to consider spontaneity impossible, the existence of causality in one form or other between things in general does not imply that any two things taken at random are necessarily causally related or causally related in a certain way. We need both positive and negative causal propositions to describe the relations between things.

... [causal logic] has three major goals, as does the study of any other type of human discourse.

(a) To define what we mean by [causality] (or its absence) and identify and classify the various forms it might take.

(b) To work out the deductive properties of [causal] propositions, i.e. how they are opposed to each other (whether or not they contradict each other, and so forth), what else can be immediately inferred from them individually (eduction), and what can be inferred from them collectively in pairs or larger numbers (syllogism).

(c) To explain how [causal] propositions are, to start with, induced from experience, or constructed from simpler propositions induced from experience.

Most endless debates about causality in the history of philosophy have arisen due to failure to first deal with technical issues. Once these goals [technical] are fulfilled, in a credible manner (i.e. under strict logical supervision), we shall have a clearer perspective on wider [epistemological and ontological] issues...

I give you the Dr.Q example:

Ben is a dog.

all dogs are green

logically Ben has to be green. Casual logic.

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