Statistics in the Media: How to Interpret and Use Them

Summary 

Statistics and statistical concepts play a crucial role in sociology, in tackling sociological questions and problems. The sociological concepts and statistical approaches aid in explaining the misinterpretation, oblivion, and the underestimation in the media domain regarding the nature and role of statistics in shaping people’s daily work and life. They set the scene for the key issues and debates that counter the views from the media and the most common myths revolving around the news and the numbers. Most media platforms fail to understand that statistics do not only imply mathematical analysis and formulation of figures, but they set a foundation for the application of the same kind of data sets in establishing logical and valid reasoning necessary for other types of news materials which shape the future of popular media. Therefore, while analyzing a viable stat spot, I became intrigued by a 2015 BBC news report regarding women who highly believe that social media platforms fuel gender violence. The report was christened, “100 Women 2015: Social media fuels gender violence.” 

Figures from the statistical report were sampled out to aid in determining the causes of the prevalent domestic violence cases and the subsequent breakups accompanying the same issues. The stat-spot is significant to the field of sociology because the study of human coexistence stems from sociological perspectives. In studying the trends concerning the tools which ignite cyber violence, the report issued by UN through BBC news indicate that mobile device and the internet serve as powerful tools which cause devastating impacts on individuals just like any physical abuse meted on women (Perasso, 2015). However, the figures arising from the report is not fixed based on the reliability and validity standards since it directs us to diverse sources to seek for more information on similar reports. For instance, some facts are derived from a survey by the Washington-based National Network to End Domestic Violence (NNEDV). The organization reported that 89% of domestic violence are technology-oriented. US-based Pew Research Center also harbor different figures indicating 66% of internet users citing social networking sites as the major harassment platform (Perasso, 2015). However, other reports suggest that 65% of women prefer not to report such issues. This contradicts with the high percentages reported by NNEDV and Pew Research Center. The report also highlights that 1 in 3 women worldwide is likely to experience some form of violence in their lifetime while 26% of women have been stalked online and 25% being targets of online sexual harassment (Perasso, 2015). The question arises on how these organizations document the high percentage yet many fear reporting cyber violence for fear of social repercussions. Moreover, there are no indicators of research methods employed in coining the above results, the study group involved, documented data, and graphs needed to support the information presented. As a result, no measures of central tendency, validity, and variability are indicated due to inadequate values and lack of graphical analyses (Best, 2012). As a stat spotter, the relevance of the study would be met if it had been hypothesized in a manner like this: “Of all the prevailing domestic and cyber violence on women, social media fuels it.” Based on this premise it would be easy to predict the independent and dependent variables. For this case, the independent variable is the social media while the dependent variable would be cyber violence. In carrying out sociological statistics, these facets are presented to aid in classifying sources for correction of systematic errors and reduction of bias. Additionally, in trying to establish reliable results, the ideology of internal consistency reliability is employed to aid in generating facts from a target audience (Best, 2013). This statistical technique enables averaging or capturing the mode on the survey group to establish reliability tests on the basis of whether the group under the study harbor similar construct. In this context, internal reliability incorporates levels of measurements and variables to determine inter-item correlation. 

In demonstrating my skills as a stat-spotter, a wide spectrum of aspects come into play. In stat spotting, one ought to seek the truth to avoid falling victim on someone else’s misinterpretation. Developing a critical mindset is crucial in the identification and avoidance of the shock value of false statistics. One is supposed to question the eligibility of the data at hand and question the purpose and the viewpoint of the information. This is also achieved by cross checking the source of the material for credibility while also trying to figure out who else is reporting similar facts. Here, it is pertinent to check whether the figures have been selected for dispatch by the popular news publishers or organizations such as CNN, BBC, or Reuters (Cushion, Lewis & Callaghan, 2017). However, there is also a possibility that fake news and figures get falsified in newspapers and web pages to reflect the names of the famous news organizations, and so it is important to confirm first from the legit homepages of these organizations for verification purposes. Cross examining for fake images and examining the evidence therein is also the best practice that should be incorporated in the process of stat-spotting. 

Critique 

The figures presented by diverse research organization on domestic violence are not consistent and this raises questions on what Best terms as Questionable Numbers. The knowledge acquired in sociology aids in spotting questionable figures and in the establishment of facts regarding statistics (Best 2008, p.3-6). Focusing on my stat spot, the news present figures without any attached references. Instead, it gives directives to other similar reports which also present different figures, hence it is upon the reader to conduct a sophisticated data investigation which delves into the secondary data in the news media (Best, 2012). The figures from the BBC news indicated 89% which overwhelmed the figures of victims who prefer not to disclose the information on cyber violence. The dubious figures according to Best are sometimes guesses arising from big round numbers. Otherwise, it is solely the task of a journalist or the reader to interpret data on their own which in turn may result in biases. The statistics may seem plausible to some extent but we are not certain whether they are right because according to Bests, it is necessary to establish the individual who tested and documented these figures as facts. Best suggests that, numbers do not just exist in nature; some human effort must be involved, therefore, knowing the person who did the counting and the reasons behind is crucial (Best 2012, p. 27-40). The statistics also fail to captures Bests’ aspect on measurement because we are not given the procedures and how the researcher did the counting (Best, 2013). We have just been bombarded with numbers which are subject to human alterations, thus, a lot of dubious data is evident in the statistical analyses. The news also do not present figures represented by these percentages and this according to Best may be misleading since we do not get the exact number of women who claim to be victims of social media platforms. Utilizing percentages without the actual figures is referred to as rhetorical flourish and such figures are subject to repetitive analyses based on already conducted and tested statistical reports. 

The statistics are independent since they have not been subjected to comparison with other figures in the consequent years to establish consistency, hence, we may not decipher whether they disagree or they are just manipulated results from the bureaucratic routines (Best 2012, p. 86-99). Moral formation is regarded as the building block of the traditional arts education and call for the integration of a prophet’s eye in every undertaking. Therefore, as much as we desire accurate and revised data, we ought to appreciate the individuals who have taken a bold move taken by people in producing, processing, and reporting the raw data. However, I would suggest that the media chose the right kind of information to dispense to the public and only accept legit data which have been approved, chose how to repackage it as news and disseminate them. I have learnt that the statistics we come into contact with are results arising from people’s choices and if they had made different choices from the ones in the domain of the people, then the results would be different. Therefore, we can’t deny these facts but try to source for sufficient information since there is no shortage of questionable statistics. 

References 

Best, J. (2012).  Damned lies and statistics: Untangling numbers from the media, politicians, and activists . Univ of California Press. 

Best, J. (2013).  Stat-spotting: A field guide to identifying dubious data . Univ. of California Press. 

Cushion, S., Lewis, J., & Callaghan, R. (2017). Data journalism, impartiality and statistical claims: Towards more independent scrutiny in news reporting.  Journalism Practice ,  11 (10), 1198-1215. 

Perasso, V. (2015). 100 women 2015: Social media ‘fuels gender violence’.  BBC News .