“Visualizing Uncertainty about the Future” as stated by Wickham (2016), describes some of the encounters that are related with interconnecting future uncertainties to confuse audience through the use of possibilities. Statistical methodologies are to communicate the concept of chances to people of a number of diversified proficiency, have been planned, and this encompasses the application of graphics visualization as a demonstrative of a number of occasions with the core objective of enticing the consideration and similarly time informative to the audience. Likewise, infographics have adjusted to deliver info regarding uncertainty with tree map as a result of the accessibility to online data. Scientific discrepancy or restricted info are encounters that are in sharing Uncertainties of likelihoods and this ascends from inappropriate interpretation of multifaceted data. The evaluation of the audience by use of experiments and tests are suggested and evading the application of complex 3D charts, are to reiterate towards proper and final design. Descriptive Summary & Essential Review Communicating uncertainty by using words and numbers Many a time, the targeted audiences do interpret words that are used to convey message poorly. For instance, uncertainty is realized when there is illiteracy and language issues. This is probable when the nature of the words used to describe the state of the situation are not correctly understood. For example, tough vocabularies used in the conveying process. Likewise, there are always numerical issues, the data given in numerals like percentages used in adverts are sometimes not realize. In case there is need for precision, then numerical data presentation can be the most applicable way. Even, it is still a challenge to the audience who are not knowledgeable in numeric. Besides, the way the information is framed to the targeted audiences. This is an issue that is mostly realized in adverts. For instance, an advert can give false information about a product and it content, like: an advert of food can be sometimes being given as 95% free of fat. This is to convey positivity to the consumers with regards to the product and convince them to buy. This therefore leads to unsureness when the reality is well known about the same product on advert. Another case can be the results about a kind of surgery that is renowned to be risky. This most depend on geographical locations, like in the U.S, a cardiac surgery rates are conveyed in terms of mortality whereas in the United Kingdom, the outcome is gives an impression since the survival rates are the ones recorded. For the uncertainty be avoided, the possibilities should be given in frequencies (Yoe, 2016). Similarly, bar charts can also be used in date representations since they are good in giving comparisons that are robust. Bar charts give the information 1 required in full details and not partly. This makes it to be one of the most applicable way in representing data I order to avoid unpredictability. For instance, bar charts have been used by NASA, like in their recent analysis about space exploration, they used bar charts to show the probability of minimal chances of reaching the 25th launch. In addition, certain studies illustrate that a simple icon array when applied in analysis, it gives more details than bar charts since it takes care of the denominator. Likewise, it favors the audiences that have low numeracy. Furthermore, line graphs can as well be used since they are easy to understand and illustrate how the specified probability can vary with time (Hancock et al., 2015). Similarly, natural frequencies are better than representations in percentages in cases of giving information about a biomedical condition. It conveys the required data in wholly but not part. The percentages are always difficult for some audiences to understand, but when an icon array is appended with the use of tree diagrams, it makes it very simple to comprehend by various audiences since there is evidence of how the probabilities are worked out. Representing Uncertainty about Continuous Quantities The tabulation of a continuous unpredictability can be represented by use of statistical summary, which involves mean, inter-quartile range, median, variance and many more. In most cases, the data representation does not effectively attempt to improve understanding to the audience. Hence, there is an evidence of uncertainty to audience since data are mostly misrepresented by various methods (Gregory et al., 2016). Infographics This is a kind of representation of data that can be easily seen by audience. Generally, it has been influenced by the design of the minimalist, who stresses a lack of disorder, concern on composition, clear lines and so on. The designers basically are concerned with the art of science with much creativity but not experiential evaluation. Recently, modernizations of infographics can be modified to converse uncertainty. An illustration is that various proceedings can be in a given word cloud, having a font size that has a proportionality to the probability. For instance, the infographics have impacted immensely on animations, development of both complex and large sets of data whereby there is encouragement of interactivity. Moreover, there are numerous remunerations of interactivity. The user’s understanding is improved since there is practical interaction with the required data rather than passiveness, which is basically essential in encountering the variances in numeracy. Additionally, interactive visuals can familiarize to the preferences and ability of the user and can as well offer assessment and response. However, the application of interactive visuals can be limited as result of lack of basic know-how in software compatibility and user skills (Mtsweni et al., 2016). What if we’re uncertain about probabilities? Many a time, uncertainty in possibilities can ascend from statistical faults or rather partial data, disagreement in scientific analyses, ignorance and many more. Furthermore, some research illustrate that certain people may accept an 2 additional credit of vagueness while those with poor numeracy may be suspicious and confused. Besides, sampling error in statistics may be conversed by use of skills on visualizing constant possibility distributions that had be outlined initially (Hillson, 2017). What Further Research is Needed? Even various research has been conducted in the past, there is need to explore more in this field. More complex analyses are needed in order to assist in improving understanding and preferences of assess. Similarly, we need keen case studies that describe much on the evaluation and development of particular examples in a given rage of framework. What about deeper uncertainties? It is dangerous for a society to be exposed to deeper uncertainty unlike the reflection on measures and probabilities of statistical error. For instance, deepsea drilling, nuclear waste disposal, climate change and so on, are frequently characterized by ignorance, fundamental disagreements. The understanding of the people on the hazards is dependent on the beliefs in how the world works. Conclusion In conclusion, it is essential and effective to make use of various methods like infographics, descriptive statistics and graphics visualization. Basically, the proper use of graphics visualization is critical in conveying info to the audience since it enhance the means of comprehending in audiences from different backgrounds. It aims at bringing the way of interacting, visualizing, and improving understanding amongst various audiences. Besides, there is no specific method that is appropriate in conveying info to various audiences. There must be variations that will cater for numerous group of people that the information is to reach. Nonetheless, there should be keenness whenever communicating statistics to different groups of audiences. The misuse of words or terms, for instance “likely” should be avoided in order to avoid uncertainty amongst the audiences. There should be proper use of words when giving statistics. In addition, in as much as we may want to impress our audience when advertising, we should not give info involving percentages that have ambiguity. Eventually, it will cause unpredictability such that in future, there will be no trust from the audience that the vague information was delivered to initially. References Gregory, J. R., Noshadravan, A., Olivetti, E. A., & Kirchain, R. E., 2016. A methodology for robust comparative life cycle assessments incorporating uncertainty. Environmental science & technology, pp. 6397-6405. Hancock, A. B., & Rubin, B. A., 2015. Influence of communication partner’s gender on language. Journal of Language and Social Psychology,pp. 46-64. Hillson, D. (2017). Exploiting future uncertainty: creating value from risk. Routledge. Mtsweni, E. S., H¨orne, T., & van der Poll, J. A., 2016. Soft Skills for Software Project Team Members. International Journal of Computer Theory and Engineering, pp.150-155. Wickham, H., 2016. ggplot2: elegant graphics for data analysis. Springer. 3 Yoe, C., 2016. Primer on risk analysis: decision making under uncertainty. CRC press.
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