As I am about halfway done The
Signal and the Noise, I must say that I am thoroughly enjoying it, and it thus
far has been my favorite book I have read for this blog. Nate Silver, due to
his background as a statistician rather than a writer (See first post for this
blog) brings a very unique writing style to the book. I find it very
interesting to read about the unique viewpoints he looks at things through. In
his opening chapter, he talks about Johannes Guttenberg, he then goes on to
talk about how Guttenberg had invented the printing press. His reasoning for
telling the story of Guttenberg was, as Silver says on page 2, “Johannes
Guttenberg’s invention in 1440 made information available to the masses, and
the explosion of ideas produced had unintended consequences.” Silver is that the
printing press led to a spike in information which in effect led to a spike in
technology which increased the amount of information we have today, but the
unintended causes is that today we have more information than we need when
solving the majority of things. With a
plethora of information today, we need to be able to separate the information
that is real evidence, which he refers to as the signal, and the information
that distracts us from the evidence, which he refers to as the noise. Silver
uses this book to analyze people’s predictions. He focus on wide variety which
jumps from predictions about what the economy will do, what Dustin Pedroia will
do in his baseball career, what the weather will be like, to the chances of an
earthquake happening.
I particularly enjoy the similes and analogies
he uses to illustrate complicated events in simpler way. In example of this
would be why house prices had increased such a huge amount and made them
unaffordable to many Americans. He introduces the terms negative and positive
feedback. To describe negative feedback, his example is kids running a lemonade
stand, and if kids across the street open up a stand, the price of the original
stands lemonade will more than likely go down due to competition. This would be
an example of negative feedback, and then he describes the housing industry as
having positive feedback, as to determine the price of house, we often use
comparisons, so if one house’s price rises, another few probably will, which
will cause another few after that, until the price of the average home has
skyrocketed and the market has imploded. He humorously states the effect of
positive feedback on a lemonade stand, writing on page 30, “Eventually you’re
charging 46,000 for a glass of lemonade-the average income in the United States
each year-and all 300 million Americans are lined up around the block to get
their fix.
I also think he does a very good job of
describing how “the noise” is very often our own human bias. He describes on
page 137, with a graph, he how weatherman often will stray from predicting
there is an exactly 50% chance of rain, as then it is a toss-up and the
listeners will be disappointed they won’t know if it will rain tomorrow. Silver
also had discovered that when there is a 50% chance of rain and weatherman
don’t want to say 50%, they will more often than not go to 60%. The reason
behind this, as Silver explains, is that if you say it probably isn’t going to
rain and it does, then you ruin everyone’s picnic, however if you say it’s
going to rain, and it doesn’t, then people are delighted and view it as an
“extra” day of sunlight.
He also mentions how on a TV show
which features former politicians debating what will occur next in political
races, they often tend to dramatize for the television. For example, Silver
found out that if one guy said that something was certainly going to occur, it
would only occur about 75% of the time. He also keyed in on an episode in the
week leading up to the Obama-McCain election, in which out of the four
contestants, only one said Obama would win in a large margin, as he was favored
to and as he did, and the other three either gave Obama a slight advantage or
said it was too close to call. Their goal of this, as Silver writes, is to make
it seem the race is much closer than it actually is, so people will continue to
tune in to hear updates.
This book is similar to Malcolm
Gladwell’s books, however, rather than scientific studies, this book is a lot
more statistically and mathematically focused, as many of the chapters are
filled with graphs, charts and tables. However, I think he uses graphs, charts
and tables very effectively. A great example of this is on page 81-83, in which
he presents two graphs of the average baseball player’s performance in relation
to his age. He first presents a graph that would accurately represent the curve
that a player goes through as he rises at a younger age until about 27 years
old, and then they start to decline. Then, two page later he presents a “noisy”
graph that is misleading and that you cannot draw as many conclusion from.
(Accurate graph on the left, noisy graph on the right)
As I had stated
earlier, I am greatly enjoying this book and I look forward to finishing it.
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