Statistics with Probability

Final Draft Sergey Padalka

As I was reading “The Philosophy of Data” by David Brooks on New York Times¹, the topic which got me into thinking about as to in which situations should we solely rely on instinctive pattern recognition and which situation should we ignore instinct and follow the data. Within the column, David Brooks basically give examples of following data and ignoring intuition and vice versa.

Venturing into answering Brooks question and my research topic, I found this article titled, “Big Data vs. Intuition-Why Coexistence is important,²” Which basically answers the main topic question, in most situations data and intuition will have to work together, side by side. One can’t rely on data or intuition alone. As the author of the article claimed, “…intuition drives big data” that if we create algorithms to study a specific occurrence then it is not a creation of natural generation. This specific occurrence someone thought was worth looking into therefore created the algorithms.  In the final part of this assignment, I shall go in depth with data and studies which supports the coexistence of data and intuition.

I shall explain as to what it means by intuition in the context of decision-making. The intuitive mode of thinking characterized by three key features: subconscious mind dominates the process of formulating or rationalizing the final results. The information is not processed in a logical sequence of thoughts but instead as parallel (more as a whole). Last but not least, emotions are connected with you so that means that an option may consider may not feel right even though you don’t have a clear proof of that.³

Intuition is needed when speedy response are required and fast paced change or the problem is poorly structured that you don’t have enough time to go through rational analysis. On the other hand, rational analysis is very important to be used when you have clear criteria and have to deal with extensive quantitative data, quantitative finance. Intuition works best when used effectively. For example, collecting data and doing homework so that intuition will be a big help navigating through faster on much of unstructured data.⁴

Coexistence of data and intuition are very important. I read a long discussion on, “The End of Intuition?” ⁵ By Paul Pellman and it can be summarized as that the answers data can provide are only as good as the question we present. In order to ask question in the right way, it requires both intuition and the relevant data about the industry.

Sources:
<sup>1. http://www.nytimes.com/2013/02/05/opinion/brooks-the-philosophy-of-data.html
2. http://www.uncleguidosfacts.com/2013/02/data-vs-intuition.html
3. http://www.time-management-guide.com/intuition-decision-making.html
4. http://www.time-management-guide.com/intuition-decision-making.html
5. http://m6d.com/2013/03/13/the-end-of-intuition-a-discussion-with-paul-pellman/</sup>

Part 3

1. The length (quality) of your paper is on the low side. You were suppose to incorporate the research you have done (part 2) into the response piece (part 1) which is on average 400 to 800 words. The new section (Part 2) should have add roughly 200-400 words to your Part 1. Total for the piece should be roughly 600-1000 words, the lower end if you have few quotes and/or paraphrases, the upper end otherwise. You have 851 words which is good. But you only mentioned 2 sentences from your part 1 assignment.
2. In a David Brooks’ column, “The Philosophy of Data,” he claims that data performs well in two areas: First, data “is really good at exposing when out intuitive view of reality is wrong” and “Second, it can illuminate patterns of behaviors we have not yet noticed” (Brooks, 2013). – two long of a sentence- run on sentence, try making it into two sentences.
3. “big data does poorly” and in many aspects that it cannot always handle big problems, -reword this sentence. It is confusing.
4. I would suggest you change the way you began your introduction…you went straight into mentioning “the result of your study about data” reword it, it’s confusing…What study? What data? These questions come to mind as a reader when reading your paper. You should specify what the study is and present the data.
5. First talk about Brook’s two articles, then your study (your two articles) and data as well as the result and how it relates to Brook’s articles. Then your conclusion.
6. You have the same transition word “also” used twice in two sentences that are one after another.
7. You have used the word “However” twice when starting of your sentence and have not explained your quotes. I see you mentioned and critiqued that as a comment on my paper but haven’t done the same for your own =) You can use however, since it is a transition word…also quotes do not have to be explained, the man who came to our class regarding writing techniques had told us this…he said that if we put a quote we don’t have to explain it since the quote states the idea that you want to portray and explaining the quote will be repetition. You have to use either, or but not both. Also I noticed that you did not use a thesis sentence either as you critiqued in my paper at the end of your introduction instead you talked about Brook’s second article. I don’t think we need a thesis since this is paper and not a formatted essay. We were told to have fun with this assignment in regards to learning more about the usage of data.
8. State your study clearly, the data found on the study and the result of the study. It’s very confusing. You talk about weather, but what exactly about weather is being studied …what are the two components the vice versa such as in Brook’s example the result if the CEO stayed or if he had left would be the two vice versa components being looked at and the data that follows it as well as the result of each and which was better in regards to data. As a reader it’s very confusing to establish this in your paper. I suggest you organize it to make it clearer to view these points and your transition to each sentence.
9. What is your research based upon…what topic in regards to Brook’s?….I know it’s about weather but what about weather…. State your focus clearly …what were you trying to portray? I agree weather has a lot to do with data but I don’t get the reasoning of why you chose topic. It would be nice to state for your readers to know and which of Brook’s statements or examples in his two articles brought you to this research? It needs to be stated clearer.
I find your topic to be vague rather than precise. Try working with it so it’s more precise in regards to your focus… Keep in mind Brook’s mentioned that it depends on that individual and there situation in regards to data.
10. “we then could decide when we are supposed to provide it”…weather is provided everyday…weatherman can’t choose when to provide it and when not too. =)

Overall your paper was good. I loved the way you wrote just need to be more clearer and organized and have more input on Brook’s articles from Part 1

I am writing about the aspect of hot streaks in David Brooks article “The Philosophy of Data.” He states “Every person who plays basketball and nearly every person who watches it believes that players go through  hot streaks, when they are in the groove and  cold streaks, when they are just not feeling it”. Through my research, I have found that it’s more complicated than just whether if a player is feeling it or not, and that there are many other factors which come into play; the period of a “Hot streak,” for a player is more related to consistently winning and the winning streaks for the team during that period, than just the input from that one player.

I have ascertained from data collected from the statistics of five teams, who consistently won and have had long winning streaks, the fact that players with hot streaks are generated more often, and exist more on those hot teams; the first team the U.C.L.A. Bruins basketball team who won 88 straight games between 1971 and 1974, the second team the New England Patriots football team who won 18 straight games between 2003 and 2004, the third team the UCONN women’s basketball team won 90 games straight between November 2008 and December 2010, the fourth team the Miami Heat basketball team won 27 straight games between February and March or this year, and finally the New York Knicks basketball team who had an 13 game winning streak just recently.

In the case of the men’s U.C.L.A. basketball team, they had several strong players, and if one didn’t play well in a game the rest of the team took up the slack. The dominance and confidence level they built during the streak was high, that along with their intense game plan, gave all the players more chances to be hot when they could, and if not, then other members of the team could take that occasion and try to get hot and keep the team’s winning streak going.

In the case of the New England football team, their quarter back Tom Brady, who you could say was hot during New England’s winning streak, had his heat turned down by the New York Giants in Super Bowl XLll where the win streak was broken in a 17-14 loss. They found a way to beat the Giants in their final game of the regular season, but that win led the Giants to better prepare for a possible rematch in the Super Bowl, which ironically took place that season, by formulating a defensive plan for that game in which they prevented Brady from getting hot. This is more evidence that a player cannot have a forum for being hot unless his or the opposing team affords him one.

In the case of the UCONN woman’s basketball team, one player Maya Moore can be considered to be a key component in the win streak. She played an overall role; offense and defense that contributed heavily in all the wins. She was not the leading scorer in all the games during the streak, the rest of the team bonded around her and played their best because of the confidence and discipline Moore displayed. In the game that ended the streak Moore began her scoring late in the first half, the rest of the team didn’t have her good play or another leader to motivate them that day, and this eventually led to the lost. I don’t believe being hot or not contributed to the loss; she had slow starts in games previous to that one, and the team just filled in until she heated up, they could not do that in the game that broke the streak.

In the case of the Miami Heat basketball team, the number of dominate players on the team was a big help in establishing their win streak. I personally watched most of the games live. When all your players produce at a high rate, it doesn’t really matter if one or two are hot, the total sum of points is always going to be high, but it does allow for a player to become more comfortable and find those hot streaks more often. In the game that ended the streak, they ran into a Chicago Bull’s team who played good defense and found a way to keep those Miami stars from getting very hot, while they were putting the heat on Miami.

In the case of the New York Knicks basketball team, I also had the benefit of watching the games live, the players for the team were more consistent with their play, good defense and ball movement, it was more  of the cohesiveness of the team than just the players being hot. Again here good play leads to a comfort state that promotes winning and hot streaks. In the game in which the streak was ended, I noticed something else related to streaks; they played the Chicago Bulls, the same team who ended Miami’s 27 game winning streak, the Knicks were visually tired by the fourth quarter after big runs of high scoring at the beginning of both half’s. They expended themselves and did not have the stamina to match the Chicago run in the fourth quarter. It was obvious some Knick players were so called hot and feeling it, but in the end a lack of energy was their downfall. No matter how hot you are, a lack of stamina will be a big negative.

In all five cases, the opportunities for a player to go on a hot streak increased greatly when their team was winning, everyone one on a team believes that the team can win, and they want to win! Why would they play the game if this wasn’t true? It’s the team’s cohesion and dedication towards a good work ethic and game planning in that sport that determines who’s going to be hot or not and how much it leads to winning. Without a winning spirit it’s hard to be on a hot streak night in and night out. Being hot needs something to be built on; winning is the perfect ingredient.

Let’s look at LeBron James, who before Miami played for Cleveland. He played well in Cleveland and was considered to be on a hot streak most of the time, but he was unhappy because they didn’t win a championship and he had no problem expressing that. When he jumped ship, making Cleveland fans very unhappy, he went to Miami were more superstars were assembled with him, and where winning has led to a championship, he has now reached a potential point for a permanent hot streak, just as Michael Jordan did with the Bulls.

Michael Jordan in his physical prime was as accustomed to playing basketball as the rest of the world was to eating and drinking. How can anyone account for or calculate the fact that he had other players on his team, some of them had been in the league for years, playing at a level that they never reached before; playing their best, “just like Mike,” to so many championships?

I would now like to say something about my main argument against any connection between human actions, and probability and statistics. People have not and never will be able to be analyzed to predict future actions; it is a natural human reaction of emotion for any given event presented at a particular time! This can change from minute to minute.

Even though we are only somewhat discrete with our emotions, we can find better ways to deal with any situation; no matter if they produce good or bad inputs to our brains reaction center, by focusing on trying not to put ourselves in situations of possible stress. One good way of avoiding stress is by completing all tasks set for you on any day, and completing them in a timely fashion. The stress of feeling that you are late, and you might miss out on something is false and created by you alone; as you rush to complete your task, the people you are dealing as you go along may not know you are late and  quite frankly probably don’t care. You’re late, and only you had the power to change that.

I do agree with the point made by David Brooks about the making a foul shot either after making or missing several of them before. I believe a player has the same chance of making a foul shot every time, the factors involved are the physical and mental conditioning at the time they shoot. Putting in the proper focus and energy are the determinants. The same factors which dictate a winning streak, which is a major factor of hot streaks. It has very little to do with probability and statistics! Data for a player or a team has to be collected for some time, years, before it can be constructed to give possibilities for game play, but it may not be accurate because it can’t predict how a player might feel that day and how it will affect his play. I certainly would not use that data to place a bet.

References:

“The Philosophy of Data” by David Brooks New York Times, February 4, 2013

“Miami Heat Winning Streak by the Numbers” Kurt Badenhausen Forbs Magazine March 28, 2013  http://www.forbes.com/sites/kurtbadenhausen/2013/03/28/miami-heat-win-streak-by-the-numbers/

“Timeline of the Miami Heat’s Winning Streak” New York Times March 28, 2013

“Miami Heat’s winning streak ends at 27 in Chicago” Andrew Seligman Time Magazine March 27, 2013

http://keepingscore.blogs.time.com/2013/03/27/miami-heats-27-game-winning-streak-snapped-by-chicago-bulls-101-97/

“Connecticut woman’s basketball 90-game winning streak snapped by No- 9 Stanford in 71-59 defeat” Associated Press December 31, 2010 http://www.nydailynews.com/sports/college/connecticut-women-basketball-90-game-win-streak-snapped-9-stanford-71-59-defeat-article-1.471214

“Connecticut Huskies’ 90-Game Win Streak” ESPNW December 5. 2012 http://espn.go.com/ncw/topics/_/page/uconn-huskies-win-streak

“UCONN Woman Own the Longest Streak” Jere Longman December 25, 2010   http://www.nytimes.com/2010/12/22/sports/ncaabasketball/22uconn.html

“Game By Game: The UCLA winning streak, from 1 to 88” Tom Hoffarth December 19, 2010 Daily News Los Angeles http://www.dailynews.com/sports/ci_16898177

“Confidence: How Winning Streaks and Losing Streaks Begin and End” Book Review by Frumi Rachel Barr MBA, Ph.D. – Executive Coach, Break through Consulting http://breakthroughconsulting.com/executive_coaches.html