Reflection on Signal of the noise by nate silver - Book Report/Review Example

Reflection of the Signal and the Noise The Signal and the Noise is a novel by Nate Silver, an American statistician who is famously known for correctly predicting the winners of all the 50 states in the United States of America. The book was published before the 2010 US presidential election and became a bestseller instantly. This paper is a reflection of The Signal and the Noise: Why So Many Predictions Fail — but Some Don't. The book title that Nate Silver used was informative of the contents of the book.

The name Signal and the Noise has a hidden meaning where the author tries to tell the reader to differentiate from something tangible and that which is not. The subtitle Why So Many Predictions Fail — but Some Don't, the reader learns the core philosophy that the author explores, which is an honest analysis of the performance of the models of prediction. This title introduces the reader to the details that the author will be addressing in the book (Silver 12). Nate Silver has included case studies in the book that deal with issues of basketball, polling, Gross Domestic Product (GDP), pandemic flu, poker, chess, stock market, terrorism and global warming.

In these case studies, Silver shows the use of various prediction systems and their successes or failures. For example, in the chapter that deals with baseball player performance prediction systems, Silver writes PECOTA Versus Scouts: Scouts Win. This title is catchy and makes the reader want to know how Silver makes this prediction. Silver then goes ahead to provide the details for the reader to get a clear insight into this form of prediction (Silver 9). For Nate Silver, predictions are not just games but involve science concepts too.

He reminds readers that the current world is a world encompassed by “Big Data” that involves 2.5 quintillion bytes” that are generated every day. Despite this fact, Silver proves that a volume of data by itself does not make prediction any easier. He clearly states, “Numbers don't speak for themselves,” (Silver 45) because they need other relationships to make sense. Numbers create meanings depending on the approach used in prediction. There are patterns that are found to be random noise and there are predictions that fail.

To explain these facts, Silver says, “Unless we become aware of the biases we introduce, the returns to additional information may be minimal—or diminishing” (Silver 56). This means that one has to know the way to take out the correct signal from the noisy data, which should be the truth. The noise serves as the distraction from which the signal (truth) should be obtained. Silver notes that predictions such as those made on politics, basketball matches and other games are mostly correct or easy to make correct forecasts.

However, when it comes to predictions of issues such as hurricanes and earthquakes, most forecasts are made incorrectly because earthquakes and hurricanes occur without warning. Thus, this shows that mostly, people use similar prediction methods or models to predict issues that happen differently or conditions of occurring are different. The book is divided into two parts so that the first part deals with problems encountered in predictions while the second part involves suggestions of how people can improve their abilities of predictions.

First, Silver suggests that people should avoid overconfidence for them to clearly recognize the degree of uncertainty that is involved in predictions. He observes that the best predictions use ranges and probabilities as opposed to specific numerical figures. He advises that predictions should be made using Bayesian concepts where a mathematical rule is used to adjust a base probability figure where new evidence comes up. He presents this idea using a medical example where 1 percent of women of 40 years old have breast cancer.

He presents this example among others in a well-explained manner making complex statistical materials accessible. The most important aspect here is that the arguments and examples he gives are well researched as seen in the 56 pages of printed footnotes (Silver 215). Nate Silver’s book and the ideas in it can be sufficiently linked in medical statistics. In medical statistics, numbers are not the only concepts used in making predictions. Other aspects, such as the relationship between numbers and real world occurrences are important.

In addition, Silver’s ideas can be linked to medical statistics in the sense that medical statistics are made to make predictions in the medical field. This means that medical statistics must be well researched to make valuable and correct predictions that can be used. Medical statistics must be reached at using self-effacing, honest and correct ways that show the limits of the extent to which an occurrence is going to happen. Just as Silver notes, a clear gap between the information people know and that which they think they know must be identified even in medical statistics to make correct predictions.

Works Cited Silver, Nate. The Signal and the Noise: Why So Many Predictions Fail — but Some Don't. New York: Penguin Press HC, 2012. Print