Humans, we are set apart from other species because our brain is much more efficient at recognizing patterns. Everything we see in our everyday lives, we subconsciously analyze to find patterns or some kind of trend; even when we don’t notice that we are. For example, let’s say that an individual has had a series of bad experience involving a pool or heights; that person will at times develop a sort of defense mechanism in the form of a phobia. This is probably because statistically speaking, this person might have recognized that their chances of a poor outcome given the first input being a pool or heights are higher than accepted. I personally do agree with the article on most cases; however I do think that the future is unpredictable at times and can have spikes or distortions in pattern without notice.

The chaos theory is based on this, it basically states that at any given time in any experiment, even those involving numbers can be completely unpredictable. We humans like to relate the unknown to chaos. We like to predict anything and everything and we do so by creating statistical  data that highlights to us the trend. I enjoyed Brooks’s comment on the 2012 election campaign tactics by the Obama administration. Although I couldn’t care less about either Romney or Obama , It is irrefutable that vilification and elections go hand in hand. The reason as to why the strawman attempt by the administration did not work, in my opinion is because Romney was doing a good enough job isolating himself from the voters. Ron Paul was basically an unknown entity in respect to politics, not because he was new; but because he had no exposure by media, because of the focus on the so called red and blue party. Since we’re speaking about trends here, it would be likely for me to mention that data suggests that mostly all of our presidents have been related to one another in some way. It shocks people when I tell them that Obama and Bush are actually cousins. Bottom line to me is this: data can help us, but only to a certain degree.

A company can be having a great year and could be bankrupt the next due to some unpredictable events. Humans obsessions with keeping records of everything and decoding it meticulously in attempts of finding a pattern is an old one. It is unarguably solid but subject to spikes and distortions just as anything else is. Brooks second article was particularly enjoyable. He speaks of how data cannot take into account the human factor of emotion and he is right. Emotions themselves are unpredictable thus making results produced by emotions ultimately…unpredictable. Brooks writes about a struggling company who in all good sense should have  pulled out while they had the chance, but due to whatever reason chose to stay in and ride out the storm. In this case it worked out favorably to the company, but that’s not to say that if this experiment was repeated that it would have produced the same result. Ultimately the point being made here is that data can only tell a person so much. such is the case in politics.

Probability and statistics play a major role in politics. Actually, the counting of votes is basically statistically employing a person to be in office. Whenever one watches a news channel during election times, they are bombarded with numbers, percentages and likelihood of winning or losing. Almost as if it was less of an election and more of an off-track betting facility. A campaign consists of planning, information gathering and meticulous dissection of state by state, variation of opinions based on the reality and mindset of the people which inhabit that state.  New York for example is 60 percent democrat, 33 percent republican and the rest go to liberals and conservatives. So, with that information in hand, a republican candidate will know that in order to tip the scale in his or her favor, they will have to appease to the overwhelming democratic population of the state. Having nearly a 30 percent chance at anything is almost never a good thing. This will lead to a candidate spending more money in these kinds of areas, in which they know that they must work hard to get a vote.

A candidate makes his or her appeal to the voters because the voters are the ones who cast ballots. Consider the following groups of people: Adults, registered voters and likely voters.To discern the mood of the public any of these groups may be sampled. However, if the intent of the poll is to predict the winner of an election, the sample should be comprised of likely voters.The political composition of the sample sometimes plays a role in interpreting poll results. A sample comprised of entirely of registered Republicans would not be desirable if someone wanted to ask a question about the electorate at large. Since the electorate rarely breaks into 50% registered Republicans and 50% registered Democrats, even this type of sample may not be the best to use.

Abortion has been a key factor in the last 3 presidential elections. Candidates are careful to not give a definite answer at times, because they know that, in another part of the country, the sample populations opinion will vary from their own. I believe I must further explain this word that has been used in this essay, sampling. Sampling is taking a small portion of something rather large and making a prediction as to how the remainder of the portion will react based on the result of the tested or “sampled” subjects. This can work at times; however, it may also backfire. let’s take into consideration, the previous presidential election between Barack Obama and Mitt Romney. Mitt Romney lacked support of the latino community heading into the election. Obama on the flip-side had the majority of votes from the latino community. One of the many mistakes made by the Romney campaign was undermining the votes being lost to Obama because of this. Romney’s campaign crew sampled incorrectly. Admittedly they claimed that their numbers had predicted something completely different. A poll with a larger sample size is not necessarily the better poll. On the other hand, a sample size may be too small to state anything meaningful about public opinion. A random sample of 20 likely voters is too small to determine the direction that the entire U.S. population is leaning on an issue. Associated with the size of the sample is the margin of error. The larger the sample size, the smaller the margin of error. Surprisingly, sample sizes as small as 1000 to 2000 are typically used for polls such as Presidential approval, whose margin of error is within a couple of percentage points. The margin of error could be made

as small as desired by using a larger sample, however this would require a higher cost to conduct the poll.

       “ Statistics had it’s origins in Politics”-  The American Statistician. Brooks may or may not agree with that statement by Philip M. Hauser. One fact remains irrefutable: Probability and statistics, although a vital part in Politics, are only as good as the statisticians behind the number crunching. Even then there is “noise” and distortions in the expected results. This is because not everything can be tied to a number; such is human emotions and sometimes…just plain old luck. It is unwise to bet the farm on odds that are not in your favor, but that is un-American. We Americans, love nothing more than playing with chance and finding a way of beating the odds. When it comes to Politics, although it may have a darker side essentially, the  name of the game is still probability.

Sources:

Philip M. Hauser

The American Statistician

Vol. 27, No. 2 (Apr., 1973), pp. 68-71

http://en.wikipedia.org/wiki/Social_statistics

http://scienceblogs.com/goodmath/2006/06/28/skewing-statistics-for-politic/

The Philosophy of Data

By DAVID BROOKS

Published: February 4, 2013

What Data Can’t Do

By DAVID BROOKS

Published: February 18, 2013

Other sources include various websites (+15)