Essay Example on Verifying Sources: Establishing Credibility of Statistical Information

In the wake of fake news and misinformation spreading across the media, it is highly critical always to scrutinize a source of information for credibility. Credibility is the quality that a reference is indeed trustworthy (Rubin, & Liddy, 2006). When it applies to a source that presents statistical information, credibility is the quality of reliability in a reference. This implies that for statistical sources of information, the element of consistency is what establishes the credibility of the source. While it may seem easy to determine the reliability of any source of information, it is also involved, especially if a source is clouded in a flowery, captivating, and persuasive language. Numbers may also be deliberately altered or manipulated to induce the reader into discerning a source as credible or reliable. However, there are several ways that one can establish whether a source is trustworthy. The following are ten ways of ascertaining the credibility of a source of information.

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Source: Sources that undergo numerous reviews before being published are generally considered credible (Rubin, & Liddy, 2006). The information posted by individuals in personal blogs and sites like Wikipedia or even social media posts is never reviewed by independent researchers, especially those who have authority in the field and are hence are rarely credible.

In-depth: Information pieces of information that generally dig deeper on a source are more likely to be authentic and credible as opposed to those that present a shell of information (Rubin, & Liddy, 2006). Generally, rich and in-depth data is collectively considered as having undergone several phases of scrutiny before being presented to the reader.

Content: Content ought to be thoroughly supported by other sources, or the primary source for it to be accepted as credible. It is noteworthy that a majority of peer-reviewed sources emphasize the need for all content to be justified, authentic, and grounded. The most crucial aspect of all is the need to root the critical content with links or sources from which the reader can further verify the credibility of a source.

Format: The format of data and informational sources reveals a great deal about its credibility. Most peer-reviewed and academic sources emphasize the need to adhere to sound formatting rules both on the piece of information as well as where the data is garnered. It is increasingly important to avoid profit sources because they rarely care about credibility. The format in those sources is meant to attract and persuade a reader toward a specific self-interested end. For academic sources, the format is highly emphasized and mostly follows a scientific structure, which is often predetermined for the particular research genre.

Accurate: Sources of information, especially the profit news outlet, are fond of providing stories and retracting quickly. In the wake of the Coronavirus, the Guardian reported that the Governor of Connecticut had said that a six years child had died, and promptly retracted when they discovered that it was erroneous for the child was seven years old according to the Governor. Academic sources should also be scrutinized for veracity to establish whether the data they present is flawed. There are a series of statistical tools that one can check to verify the accuracy of data. In the wake of the coronavirus pandemic, researchers have been questioning the accuracy of Chinese numbers based on observed variance, and the trend in other places (Oxford Analytica, 2020).

Authority: It is also important to scrutinize the author of the information. One should always look for clues, such as whether the author has experience in the field. Authority also concerns the capability of the research organization or individual to conduct the study and provide the numbers.

Timeline: Timeline is also known as currency. More recent publications are considered current and hence credible as opposed to outdated sources because the information is more likely to reflect trends and practices in recent times. A source that references outdated sources apart from theoretical and historical purposes is hence more likely to incredible.

Scope: Scope is an essential aspect of considering credibility because it also determines whether the findings in a source are generalizable. A source that is broad-based and expansive in the issues it addresses is less likely to be credible than a source that is more detailed and precise in what it investigates and presents.

Recommendation: Sources that have been recommended by authorities and professionals in the field are more likely to be credible than sources that recommended by non-experts (Ge et al., 2012). However, it is always critical to remember that the fact that a source has been recommended does not imply that one should not independently scrutinize the source to establish its credibility.

Consistency: Consistency is the element of usability of a source of information or provided data. A user failure to uphold objectivity and standard in inferring from data may make the data inconsistent. Bias or prejudice, and weak data collection instruments may all make data inconsistent. Scientific and academic sources undergo rigorous testing to determine the consistency of data; hence they are more credible sources of information.

Conclusion

In summary, there are several ways that readers can establish the credibility of a source of information. A reader should scrutinize a source, its authority, and the format of data as well as the currency of the information. They should also investigate the source for accuracy, consistency, scope, and content. Sources of information that have been recommended by an expert are more likely to be credible than those who have not. Readers must thoroughly investigate a reference based on multiple cues because there still lacks a holistic technique.

References

Ge, L., Gao, J., Yu, X., Fan, W., & Zhang, A. (2012, December). Estimating local information trustworthiness via multi-source joint matrix factorization. In 2012 IEEE 12th International Conference on Data Mining (pp. 876-881). IEEE.

Oxford Analytica (2020). China's COVID-19 outbreak will weaken Xi. Emerald Expert Briefings, (oxan-db).

Rubin, V. L., & Liddy, E. D. (2006, March). Assessing the Credibility of Weblogs. In AAAI Spring Symposium: Computational Approaches to Analyzing Weblogs (pp. 187-190).