The Median Isn T The Message Analysis

In the movie Unnatural Causes: In Sickness and in Wealth, it compared the lives of four individuals, Taylor, Young, Anderson, and Turner, in different locations, race, and socioeconomic background. The scale of difference between this group of people is that it goes from financially stable and healthy individuals to individuals with lower income and poorer health. This wealth-health gradient reflects that those who have easier access to healthier lifestyles (i.e. running outside without the concern of safety) are more likely to have a higher life expectancy than those who are in living environments that are not as developed and lack healthier options of nutrition. The difference of the average life expectancy scaled down from Jim Taylor whose neighborhood had an average life expectancy of 80 years, Young’s 75.3 years,

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

People were less likely to face poor retirement if they worked in managerial or professional jobs than someone who worked in unskilled or manual occupations. This is because the people who worked in manual would have earned lower wages and would not be as likely to get a private pension. Men that are in the professional classes have a life expectancy of 80 years from birth. However men from unskilled or manual classes have a life expectancy of 78.1 years. This also effects woman’s life expectancy as woman from professional classes have a life expectancy of 85.1 compared to those who are in the unskilled or manual classes and their life expectancy if 78.1 years. Causes of death also vary from different social classes. In the higher social classes it is less likely to suffer from, lung cancer, coronary heart disease, stokes and respiratory diseases. All of these increase within social disadvantages.

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

Stephen Jay Gould analyses Paul Broca’s data of inferior women to superior men through the study of Craniometry in his piece, Women’s Brains. While Broca claims women are unintelligent when compared to men through thorough measurement of the brain; Gould realizes the accusations are false due to their combination of science to social correlation and beliefs. Gould argues that women are not inferior; they are only baring the brunt of unfair scientific research conducted to prove society beliefs. Even the most reliable scientific data and research is not valid within the study of social norms and accepted society stereotypes.

I support the idea that scientists’ theories cannot be completely objective, because scientist are people and everyone has opinions and biases not matter what they say. An example of this in the article would be how Blumenbach’s teacher, Linnaeus had his basic four classifications for humans in which had characterized them by their color, humor, and posture. His biased views really

First, there is Jim Taylor, Hospital CEO, District 16; second, Tondra Young, Clinical Lab Supervisor, District 24; lastly, Corey Anderson, Floor Technician, District 21. The population of each district decreases in average income, education level and life expectancy than its preceding district, beginning with district 16, Jim Taylor’s district. District 16 has an average combined household income of approximately $120,000/ annually. In this district, 65% of the population has a college degree and the life expectancy in this district is 82 years. Whereas, Tondra Young’s district, district 24, has an average combined household income of $70,000/annually and 15% of the population has a college degree. The life expectancy of district 24 is 75 years, that’s 7 years less than district 16. In district 21, Corey Anderson’s district, the average combined household income is less than $50,000/ annually and only 5% of the districts population have college degrees. Consequently, the life expectancy of district 21 is 70 years, 5 years less than district 24 and 12 years less than district 16 (Adelman 2008). The results of this study are indisputable: there is an obvious correlation between social/economic status and health status. As each districts average income and education level decrease, average life expectancy coincides. This leads to the next question: why does social and economic status so greatly influence health status?

Both authors have PhD and work with the Center for Medicine, Health, and Society, which makes them experts on the field. Also the data used in their examples is from recent years, which make their data reliable.

· The results of the study, the interpretation of the data by the authors and any conclusions they include at the end of the article.

Throughout this publication, Stephen Jay Gould tries to convince the reader of his argument that the claims that Broca made were simply outrageous. Even though Gould comments, “I have the greatest respect for Broca’s meticulous procedure. His numbers are sound.”, he refutes Broca’s, and his disciples, work. Gould uses a large amount of statistical data to counter Broca’s argument. He states that “In an analysis of the data for women, I found that, at an average male height and age, a woman’s brain would weight 1,212 grams. Correction for height and ages reduces Broca’s measured difference of 181 grams by more than a third, to 113 grams.” While Gould uses this to support his own data collection, he also exhibits data collected by Broca himself.

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.

The authors relied heavily on two studies to create their argument. The first study mentioned was the Pinto et al article. In this study, "Pinto and colleagues (5) assessed the

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.

So many people complain about all the math, how boring it is, and how everything about it is awful. This is mostly just seems like it is because they don’t understand. Even Alan Smith reportedly was awful at statistics and computer programming, but his quiz which, changed the perspective of over 250,000 people, managed to change his mind. This is fascinating to me. Although I have never taken statistics, I have a predetermined mindset that statistics is not worth taking. I have always been told to take calculus or linguistics or anything else but statistics, because every other class is easier and has a more defined purpose, especially for my major. No one has ever mentioned the impact that statistics can have on people, however. That is what made this Ted Talk so interesting.

However, some researchers, such as Steven Gould (1978), suggest that prejudice was used in the scientific method used by Broca, and test subjects may have been specifically selected to validate the social beliefs of the time rather than to test an unproven theory.