Read The Two Articles: Predictive Probes And New Test 204817

Read The Two Articles Predictive Probes And New Test Tells Whom A

Read the two articles "Predictive Probes", and "New Test Tells Whom a Crippling Disease Will Hit—and When" from the textbook and write two separate analytical summaries. These articles can be found in the chapter titled: Deciding to accept an argument: Compare the evidence. This assignment has two parts. Part 1—First Article Write an analytical summary of the article focusing on the article’s main claims. Include the following: Identify the three ways the author uses evidence to support assertions. Identify the places where evidence is employed as well as how the author uses this evidence. Discuss evidence "as the reason" vs. "the support for the reason." Also discuss evidence as dependent on the issue/context. Analyze how the author signals this usage through elements such as word choices, transitions, or logical connections. Part 2—Second Article Write an analytical summary of the article focusing on the article’s main claims. Include the following: Identify the author’s use of the three elements: experiment, correlation, and speculation to support assertions. Analyze how the author signals the use of these elements through language. For example, word choices, transitions, or logical connections. Write a 4–5-page paper in Word format. Apply APA standards to citation of sources.

Paper For Above instruction

The assignment requires analyzing two articles—"Predictive Probes" and "New Test Tells Whom a Crippling Disease Will Hit—and When"—focusing on how evidence is used to support main claims. The primary goal is to understand the types of evidence used, how the author employs it within different contexts, and how language signals these techniques. The analysis should be structured into two parts, each dedicated to one article, culminating in a comprehensive 4–5-page paper formatted according to APA standards.

In the first article, "Predictive Probes," the author primarily employs three methods of evidence to bolster assertions: empirical data, logical reasoning, and illustrative examples. Empirical data, such as statistical findings or experimental results, serve as concrete foundations for claims about the effectiveness of predictive probes. The author employs this evidence by presenting data early in the article to establish credibility and support assertions about the predictive accuracy of the probes. For example, the author cites specific study results showing the probes’ success rates, using quantitative data as "the reason" for advocating their efficacy.

Logical reasoning is used to connect evidence with conclusions, often through explicit transitions like "therefore" and "thus." These logical connectors signal that data is not merely supporting evidence but also integral to the reasoning process that leads to the main claims. Additionally, illustrative examples—such as case studies or hypothetical scenarios—are used to contextualize the data, making abstract data more tangible and relatable. Here, evidence functions as "support for the reason," providing illustrative backing that bolsters the logical argument.

The article signals the distinction between evidence as the reason and as support through specific word choices and transitional phrases. When the author introduces data with phrases like "research indicates" or "studies show," it signals that empirical data serve as the primary reasons underlying the claims. Conversely, when examples are introduced with phrases like "for instance" or "consider a case where," they function as support for the broader reason, adding contextual clarity rather than establishing causality directly.

In the second article, "New Test Tells Whom a Crippling Disease Will Hit—and When," the author employs three core elements—experiment, correlation, and speculation—to support assertions about the predictive capabilities of the new test. The use of experiments is signaled through language emphasizing controlled studies, such as "clinical trials demonstrated" or "during a randomized study," indicating rigorous testing of the test's reliability.

Correlation is employed to suggest associations between biomarkers or genetic markers and disease onset or progression. The author signals this through phrases like "there is a significant correlation between" or "data shows a strong link," implying a statistical relationship that supports predictive claims. The language often emphasizes strength and significance, such as "highly predictive" or "notable correlation," to underscore the evidence's strength.

Finally, speculation is present when the author discusses potential future developments or interpretations of current data. Language markers include phrases like "it is possible that," "may indicate," or "future research could reveal," signaling that these claims are provisional and not yet confirmed by direct evidence. These speculative statements are often tempered with cautious language, reflecting the tentative nature of some conclusions.

The author signals these different evidence types through transitions, modal verbs (may, might, could), and hedging phrases that indicate degrees of certainty. For instance, the transition "however" often introduces a discussion of limitations or alternative explanations, signaling a nuanced use of evidence. Likewise, the use of conditional language or future tense suggests speculation, differentiating it from empirical findings and correlations.

Overall, these articles demonstrate the nuanced ways in which evidence supports scientific claims, with authors carefully signaling the nature and strength of their evidence through language and logical cues. The first article emphasizes empirical and logical support, while the second leans on experimental data, correlations, and cautious speculation to build its case. Understanding these distinctions enhances critical reading and evaluation of scientific arguments, highlighting how language functions as a key tool in conveying certainty, support, and therefrom the strength of an argument.

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