In This Article Edwards Attacks the Cosmological Argument, Specifically Aquinas's

question 8

True/False

In this article Edwards attacks the cosmological argument, specifically Aquinas's causal and contingency versions, holding that the argument fails at several points. Against the causal argument, he argues that the premise asserting the impossibility of an infinite series is false. Even if the argument were sound, he says, it would not prove the existence of a single first cause because a plurality of causes cannot be ruled out. Furthermore, the argument is not helped by the theist's distinction between causes that bring something into existence (causes in fieri) and causes that sustain something in existence (causes in esse). Some defend the causal argument by insisting that even if there were an infinite series of causes, there still must be an ultimate cause of the series as a whole. Edwards counters that such notions rest on the "erroneous assumption that the series is something over and above the members of which it is composed." Against the contingency argument, Edwards maintains that to explain a contingent phenomenon, we do not need to posit a necessary being and that those who make such a demand beg the question at issue.
-Paley says that a machine must be perfect to provide evidence that it had a designer.

Recognizing the importance of voice qualities in oral presentations.

Understanding the significance of organizing information effectively in oral presentations.

Learning how to create a strong opening and closing for presentations.

Understand different patterns for organizing the body of a presentation and their applicability to various scenarios.

---

Definitions:

Bell-shaped Distribution

A graphical representation of data where the peak of the curve represents the most common occurrence, tapering off symmetrically on both sides, typical of a normal distribution.

Normal Curve

Also known as the bell curve, it is a graphical representation of a normal distribution of data where most observations cluster around the central peak and taper off symmetrically towards either end.

Extreme Scores

Values or outcomes in statistical data that are significantly higher or lower than the majority of the data set, often influencing the overall analysis and interpretations.

Central Tendency

A statistical measure that identifies a single value as representative of an entire distribution of data, such as the mean, median, or mode.