What Is Statistics Discussion?

In the video "How Statistics Fool Juries," Oxford mathematician Peter Donnelly attempts to demonstrate through a number of examples how statistics, when viewed in a common manner, can be misunderstood and how this can have legal repercussions. Through a number of thought experiments, Donnelly provides the audience with examples of how seemingly simple statistics can be misinterpreted and how many more variables must be taken into account when calculating chance. Primarily he exposes the audience to the concept of relative difference, or the difference in likelihood between two possibilities in the same scenario. He then goes on to explain that without an understanding of this concept, many juries misunderstand statistics used in trials and very often convict people based on this faulty understanding.

In Stephen Gould's article The Median Isn't the Message, there is an excellent story that displays the power that statistics can play in shaping how we think and our attitude towards certain subjects. When Gould was diagnosed with mesothelioma in 1982, he decided to research the life expectancy and was shock that it was only 8 months. Upon looking further he found that under his circumstances, he could fall under the curve much farther out, meaning a longer life expectancy.

the audience, and it is hard to put it to perspective. Therefore, a statistic is appealing to the

Increasing the power and impact of speaking through behaviors to avoid and skills to master stands the perceived thesis of Julian Treasure’s TED Talks on “How to speak so that people want to listen” (2013). Likening the human voice to learning how to master an instrument, Treasure immediately establishes ethos with his heterogeneous audience by focusing his main idea on a simple, highly relatable topic, with dynamism, directness, and a palatable sense of expertise. Strategically applying non-repetitious doses of anecdotes to support his claims, the weighty supporting ideas are lightened and balanced creating ease of listening – audience members respond with laughs and smiles solidifying their bond and entertainment to the topic.

In the video Don't Be Fooled By Bad Statistics posted by Emily Dressler three forms of bad statistics are discussed, poorly collected data, leading questions, and misuse if center. Information collected poorly will lead to misleading results and false conclusions. Dressler uses the example of data collected by researchers pertaining to magazine preference during business hours. The data is skewed because of the time of day the information was gleaned rendered the sample not representative of the entire population. Another form of bad statistics has to do with how the desired information was elicited. Leading questions may result in biased responses. Questions need to be worded carefully so the information collected is not influenced by the interviewer. Finally, the video talks about misuse of center. Data can be misleading if not appropriately analyzed. Outliers, an individual value that falls outside the overall pattern of data can prejudice the conclusion leading to incorrect assumptions. An example might be that of the man who drowned in a pond with an average dept of one inch. The pond was one quarter inch deep everywhere but in the center where there was a ten foot hole.

Mona Chalabi spoke at a ted talk convention about three ways to spot a bad stat to an audience of young adults in February 2017. She spoke about the bad nature of Statistics. Through a convincing Ted Talk “Three ways to spot a bad stat” Mona Chalabi informs the public about the dishonesty of modern day stats.

The book Freakonomics by Steven D. Levitt and Stephen J. Dubner is a book that takes you through facts and statistics that seem reasonable and logical at the beginning but soon they dissect it and show you the true side of the statistic. The whole premise of the book is to show you the “hidden side of everything. (Cover page)” Like how dropping crime rate throughout the 90’s drastically dropped seemingly overnight. This drop was associated with better policing strategies, this idea is great for reassuring the public, but is it really true? Turns out it was probably closer linked to the legalizing of abortion. The authors of Freakonomics throughout the book think outside the box in order to show you

1“The Cult of Statistical Significance” was presented at the Joint Statistical Meetings, Washington, DC, August 3rd, 2009, in a contributed session of the Section on Statistical Education. For comments Ziliak thanks many individuals, but especially Sharon Begley, Ronald Gauch, Rebecca Goldin, Danny Kaplan, Jacques Kibambe Ngoie, Sid Schwartz, Tom Siegfried, Arnold Zellner and above all Milo Schield for organizing an eyebrow-raising and standing-room only session.

have done are truthful and positive, the reader must be skeptical and cannot be sure that their statistics

In his 2013 book, Naked Statistics, Charles Wheelan explains a field that is commonly seen, commonly applied, and commonly misinterpreted: statistics. Though statistical data is ubiquitous in daily life, valid statistical conclusions are not. Wheelan reveals that when data analysis is flawed or incomplete, faulty conclusions abound. Wheelan’s work uncovers statistics’ unscrupulous potential, but also makes a key distinction between deliberate misuse and careless misreading. However, his analysis is less successful in distinguishing common sense from poor judgement, a gap that enables the very statistical issues he describes to perpetuate themselves.

In “Why Facts Don’t Change Our Minds”, written by Elizabeth Kolbert, The New Yorker staff writer explains significance of the well-known psychological phenomenon: confirmation bias. As its name implies, confirmation bias is “the tendency people have to embrace information that supports their beliefs and reject information that contradicts them” (Kolbert 4). The first section of the article is served as a simple introduction to the article with studies proving “facts don’t change our minds.” In both studies, contestants were tricked into believing deceptive information.

When studying statistics, it is important to look all aspect of it, such as the statistical ethical guidelines. Another important to look at is how Christian World view can be applied to statistics. In this essay, the following will be discussed: statistical ethical guidelines, ethical issues from a Christian World view, and ethical issues.

As a general articulation, there is very little contention that would emerge when one expresses that lying is wrong. However, when proffered theoretical circumstances start to crawl further into different circumstances, people will start to dodge and legitimize why lying would be satisfactory in specific circumstances.

In How to Lie with Statistics (Huff, 1954), Darrel Huff deciphers statistical examples and explains the means of deception that statistics and statisticians sometimes use to relay false information. Huff also conveys an underlying message of don’t believe everything you’re told, something him and my mother have in common. At first glance, a reader might think that this book will teach people how to actually lie using statistics, but that is not the case. It gives the reader a glimpse or a behind the curtain view of how easily it is to be deceived using numbers and how it is slyly achieved. Ironically he calls the book How to Lie with Statistics almost to tease his audience that the content in this book is not as it appears. To my utmost surprise, I actually rather enjoyed this book. It was a fairly simple read that was filled with new information and showed me how to look closer at statistical figures in the future. The humor was spot on so much, so that I even chuckled aloud occasionally. For the icing on the cake, I even expanded my vocabulary to learn fun words such as rotogravure.

In public speaking of any form to a diverse group of individuals, my main consideration as the speaker is my concentration on the audience that I am speaking to. In starting an effective presentation,