Question

the rooster crows at sunrise every morning, so the rooster must cause the sun to rise. this is an example of

Answer 1

The statement is an example of a logical fallacy known as a 'post hoc' fallacy, where a false assumption is made based on the order of events.

Step-by-step explanation:

The statement 'the rooster crows at sunrise every morning, so the rooster must cause the sun to rise' is an example of a logical fallacy known as a 'post hoc' fallacy. This fallacy occurs when someone falsely assumes that because one event follows another, the first event must have caused the second event. In this case, the rooster crowing comes after the sunrise, but it does not cause the sun to rise. The phenomenon of the sun rising is a result of the Earth's rotation.

Answer 2

The belief that the rooster's crowing causes the sun to rise is an example of the 'post hoc ergo propter hoc' logical fallacy, which wrongly assumes causation from sequential correlation. The rising of the sun is actually caused by the Earth's rotation, a stable phenomenon supported by scientific evidence.

Step-by-step explanation:

The statement that 'the rooster crows at sunrise every morning, so the rooster must cause the sun to rise' is an example of a logical fallacy known as post hoc ergo propter hoc, which is Latin for 'after this, therefore because of this'. This fallacy occurs when it is assumed that because one event occurs after another, the first event must be the cause of the second.

However, correlation does not imply causation. In the example, it's clear that the rooster has no influence over the sun rising; it merely crows in response to the natural change in light. In philosophical terms, we understand that the sun's rising is due to the stable phenomenon of the Earth's rotation, which has been observed and explained by science, giving us strong reason to believe that it will continue to occur, despite not being absolutely certain.

By reflecting on alternative possibilities like catastrophic events, we can appreciate the difference between extremely high probability and absolute certainty. This understanding is essential in differentiating between causation and simple correlation.