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What events are correlated but do not necessarily have causal relationship?
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Candace Okuneva
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What events are correlated but do not necessarily have a causal relationship?
A Teacher drops A box of chalk, and her chalkboard Crack a few minuets later.
Is it true if two events are indenpent then the probability of both events is less than 1?
Not necessarily.
Are mutually exclusive events independent?
Not necessarily. In fact, in binary situations they can be totally dependent - depends on the experiment.
What would lead a historian to consider two events to have a relationship of correlation rather than causation?
If the events happened around the same time but one did not cause the other
Two events have a relationship of correlation rather than causation if they?
occurred at the same time but did not influence each other.
What events are correlated but do not necessarily have a causal relationship?
A Teacher drops A box of chalk, and her chalkboard Crack a few minuets later.
Events 2 has a causal relationship with Event 1 when?
Event 1 makes Event 2 happen.
Which events have a causal relationship?
Sam had not eaten breakfast; he was hungry.
How is a wound diagnosed?
A diagnosis is made by visual examination and may be confirmed by a report of the causal events
what is the sequence of casual events in a story?
In a story, causal events typically follow a logical progression where each event is directly influenced by the preceding one. This sequence helps to drive the plot forward and create a coherent narrative. The causal events in a story establish cause-and-effect relationships that lead to the development of characters and the resolution of conflicts.
Who said the animal behaves like a scientist detecting causal relations among events and using a range of information about those events to make relevant inferences?
Rescorla
What does causalities mean?
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)
What is an example of a positive correlation that has an obvious causal relationship?
The standard answer is that a positive statistical correlation, no matter how strong, never proves anything about the causal relationship. Technically, correlations are symmetric and so the evidence is identical whether you imagine that A causes B or B causes A. Another problem is that you could have an omitted third factor C which explains both A and B. A correlation between A and B never rules out the possibility of C influencing them both. What you can sometimes say more realistically is that a strong correlation might make a proposed causal explanation more plausible. It might be evidence as part of an argument, but it's not sufficient by itself. Other parts of the argument could be exclusion of other factors (through experiments or statistical controls) and logical precedence. For example, if you had evidence that women are smarter than men, it doesn't seem likely that smartness causes gender. Similarly, events from the future don't influence events of the past; thus establishing the time sequence might also help to build a causal explanation. In short, there are few if any obvious causal relationships based on correlation alone if you want to use rigorous methods. Experiments and replication of results under diverse circumstances are the best way to show a causal relationship.
Correlations are an indication that causality is always present?
False. One of the most important rules to learn in statistics is that correlation does not equal causation. Just because two items or correlated, or linked, doesn't necessarily mean that one caused the other. For example, think about if every time you go out for a run it starts raining. Those two events may be correlated, but that doesn't mean you cause it start raining because you went for a run.
What is a cause-effect inference?
A cause-effect inference is a conclusion or assumption made about the relationship between two events or phenomena, where one event is believed to have caused or influenced the occurrence of the other. It is based on evidence and reasoning that suggests a causal relationship between the two variables.
Is it true if two events are indenpent then the probability of both events is less than 1?
Not necessarily.
What is a causal story?
A causal story is an explanation of events or outcomes that emphasizes the relationships between different factors or variables, highlighting how one factor leads to the occurrence of another. It aims to narrate how specific causes result in particular effects or consequences. Causal stories help understand the mechanics and relationships behind phenomena and are commonly used in scientific research and analysis.
