Naked Statistics : Stripping The Dread From The Data

He author also uses statistics to inform the readers with facts. For example he says, “If you’re like the typical owner, you’ll be pulling your phone out 80 times a day.” He uses statistics to inform and persuade the the

Statistics provides us with very useful tools and techniques that aide us in dealing with real world scenarios. I have been able to learn several useful concepts by studying statistics that can aide me in making rational and informed decisions that are supported by the analysis results. Statistics as a discipline is the application and development of various processes put in place to gather, interpret, and analyse the information. The quantification of biological, social, and scientific phenomenons, design and analysis of experiments and surveys, and application of

• Provide at least two examples or problem situations in which statistics was used or could be used.

Statistics, facts, data, and comparisons are absorbing and challenging to present in a way that is anything other than, well, boring. For purposes of an informational presentation, the statistics are unavoidable. However, in this

The major of statistics is used in everyday life whether it be through experiments or analyzing data for a company. With the use of statistics, it is not only important to know how to analyze data, but also how to communicate the information to others. Using the communication skills can help companies sell more products and save money on advertisements. With the advancement of digital and/or electronic communication technology, the field of statistics is growing rapidly and their findings are becoming more accurate. Post graduation I intend on working for a company doing business analytics for the products they sale. In this final paper, I will explain to you how the advancement of digital communication

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

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 article does well provide details to support main point of the author argument. In fact, the usage of statistics and other people stories may reinforced the credibility of this article. Furthermore, because of the usage of clear language and key terms that were fine defined aids the readers in understanding the message of the text. The only downfall of the article is some of statistics is not well supported with evidence or a guidelines guiding us back the origins of these statistics, although the paper is not flawless, the overall strong point of it defeats it

In order to know whether the evidence of research studies are accurate, one must be able to have a fundamental understanding in statistical analyses to determine if such descriptions and findings within manuscripts and articles are presented correctly and explicitly (Sullivan, 2012). Proper use of statistics begins with the understanding of both descriptive and inferential statistics. Correct organization and description of data characteristics from the population sample being studied leads the researcher to identify a hypothesis and formulate inferences about such characteristics. It is with inferential statistics that researchers conduct appropriate tests of significance and determine whether to accept or reject the identified null

This argument, an appeal for justice, undeniably appeals to one’s sense of fairness, but upon further scrutiny, Kourany’s unconvincing plea asks of science something that it is not equipped, and has never previously been expected, to give. Consider the science of statistics with respect to racial representation in professional sports. Do Asian-, European-, or Latin-Americans demand recompense for the statistical revelation that 76.3% of the National Basketball Association (NBA) and that 68% of the National Football League (NFL) is African-American? Of course, the fundamental difference between statistics and psychology is that statistics did not generate the athletic racial disparity in the same way that psychology generated the gender disparity. In reality, though, statistics and psychology are “guilty” of the same “misdoing,” reporting conclusions. The science of statistics cannot, and indeed should not, be disparaged for its findings, and likewise, neither should psychology. When merely reporting scientifically supported conclusions becomes a deed so unapologetic that it must be rectified, science loses its inbuilt neutrality and objectivity. Therefore, science should not be asked to remedy the effects of its

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.

Ben Davis had just completed an intensive course in Statistical Thinking for Business Improvement, which was offered to all employees of a large health maintenance organization. There was no time to celebrate, however, because he was already

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.

How much do we really know about our country, our district, or even our hometown? Are statistics really what people think? According to Alan Smith, an inaugural recipient of the Royal Statistical Society's Award for Excellence in Official Statistics, what people think is always extremely different than what the real statistic truly is. In his Ted Talk, entitled “Why We Should Love Statistics”, he discusses his study of statistics which opened up a whole new vision of the subject for me. Before watching this Ted Talk, statistics was simply a more relatable math class. After watching, I see now that statistics is also a method to connect people within communities. In fact, while statistics is a field that involves entirely numbers, it should