Final blog post for Q3 reading

In this blog i will be summarizing/analyzing pages 202-end of How Randomness Rules Our Lives. In this section Mlodinow describes the very complicated idea of assymetry. Basically you cannot predict what will happen when you are in the midst of doing something but after the fact it is exceptionally easy to criticize and say that you should've known better. Mlodinow gives many examples for this law. Such as the stock market, when you look at a chart of the most succesful managers ranked in order from most profitable to least, an analyst can saw why some did good while others did bad. However that same analyst cannot predict beforehand which managers will do good and which will do bad. This is why statistics is so important in everyday life. Because given this scenario we would be able to tell which managers would have a higher probability of doing better beforehand but we can never be 100% sure. So there is always risk and the study of statistics/probability is greatly needed to succesfully interpret the data without completly screwing up. As Mllodinow says, "i was warned not to think that i could predict or control the future" (218). Mlodinow clearly shows us that the future is a thing that cannot be predicted but can be anticipated and be prepared for.
As for pearl harbor even though the U.S. had extensive reasons to believe that Japan was preparing for an attack, why would we think pearl Harbor? The japanese had ordered their spies to do the same thing in numerous places all over. And the probability that they would attack Pearl Harbor was just an insignificant amount, however that amount still exisited therefore allowing for it to happen. "Blame is always passed around in unfortunate events" (208). Mlodinow shows readers through the 3 mile island melt down that when chance is involved and negative things happen people are allways forced to take the blame. The truth is that the 3 mile island nuclear reactor was up to date and working fine, but unfortunatly it recieved a water leak that turned of the cooling system of the reactor which enable the backup system to start which had been turned off by a janitor. So it really the janitor's fault? No it is all chance's fault.

Q3 Blog post 5

In this blog post i will be analyzing and summarizing the book The drunkard's walk, How Randomness Rules Our Lives pages 186-202. To open this section Mlodinow discusses how our views of randomness are quite inaccurate. Mlodinow uses the examples of Statscian George Langer. Langer had an expiremental lottery in which half of the subjects could choose what lottery card they got and the other half were assigned. The way you won was if your card's double was selected in a pot. He then gave the subjects a chance to trade/sell their cards. The people who choose their cards sold their cards for 4times more, even though they had the exact same probability of winning. Misconceptions such as this are extremly common in everyday life. Another such example is when presented with the number set 2,4,6,8 what is the pattern? Most people say that the numbers are increasing even numbers. However Mlodinow points out that just because there isn't an odd number in there it doesn't mean that it has to be even. As the number set could be 2,3,4,5. The cause of this misconception is explained quite well by Francis Bacon, "the human understanding once it has adopted an pinion collects any instances that confirm it" (189). This goes to show that when humans have an idea they will support it instead of trying to discredit it.
The next topic that Mlodinow touches on is how all this randomness affects our lives. "The only way i have to describe the way that randomness truly affects our lives is the title of this book, The Drunkard's Walk" (195). For example why had the U.S. not been prepared for pearl harbor? Given all the facts leading up to the event, we intercepted messages stating that spies should divide the harbor into 5 sections and classify them, then the Japanese change their radio signals when they shouldn't (this ussually signals a large scale operation) then we intercept more messages telling all diplomats to burn all of their official documents! And a large majority of U.S. officers knew about this. The explanition is due to the law of assymetry which basically states that you cannot predict random events before they happen. I will delve into more detail in my next blog post.

Q3 blog post 4

In this blog post i will be summarizing and analyzing the Drunkard's Walk how Randomness Rules our Lives pages 146- 185. In the first half of these pages Mlodinow clearly depicts how randomness in social data is actually not chaotic but very oderly "social data seemed to produce qauntifiable and predictable patterns" (152). He goes on to give us examples that seem to be complete chaos but instead are extremly orderly, as a density curve would show. You can take for example a sample of people who are driving cars one year and then count up the miles. Then the next year you can conclude that those miles will be reasonably the same, even with people completly changing what they are going to do, lets say a young girl who used to drive to school everyday gets married and stops moving. Then the milage should go down, however a young man becomes a truck driver and starts driving more often. These two would theorecticaly cancel each other out and since we take the population of a large place, (given that there isn't a significant increase in the drivers between the two years) they will equal out to be about the same. Later on in his book Mlodinow goes to show us the first person who recognized this and started to plot it. Quetelet was his name and he took samples of everything, the chest size of scottish soldiers, to the number of murders in france with what type of weapon it was committed. He found that all of these distributions were bell-shaped and represented a "normal" curve. This curve is now the basis for all statistical studies. The first recorded time this was used to a person's advantage was in the 17th century when a mathematician noticed that his baker was advertising his bread as 1000 grams and he averaged only 950. He plotted the weights of the bread he bought for a year and realized he was being cheated. Later he plotted the weights after complaining and realized that the graph was skewed to the right, meaning that the baker had been giving him a lot of heavier loaves. He complained and the baker changed his ways again.
In the second part of this reading Mlodinow talks about how random paterns are very common and confuse almost every person they come upon. To start off he talks about table turning. This is the process in which people contact the dead and turn a table after awhile the table starts to turn by itself. Scientists began to study this and realized that the people would subconsciensly start to turn the table they thought it would turn. When all the people thought it would turn in one direction they would all subconsciensly start to move the table in that direction. After much study scienctists realized that more often than not the poeple sitting at the table would all think that it would turn the same way. Mlodinow now points out that people analyze incorrectly based on percieved patterns all the time. Just as with seeing your imagination fills in the gaps. When a person looks with their eyes each eye is missing large portions of what is really there and the picture is highly pixilated, however our brain meshes the two eye views together and depixilates the image based on what it would guess is there from the combined information. Our brain does this also with statistics on things causing confusion and misconception. To counter this misconception scientists have developed a mthematical style to find patterns in samples, " To combat this misconception that people have the greater mathematicains came together and formulated a grand idea" (178). This grand idea is based on the curves from earlier and it measures the probabiblity of an event hapenning.

Q3 blog post number 3

In this blog i will be summarizing/analyzing pages 105-145 of Leonard Mlodinow's the drunkard's walk. It starts off where we left off, Pascal's death. We carry on with Thomas Bayes, a mathemetician and minister who lived during the 18th century. Bayes' greatest contribution to probability are his theories on conditional probability. That is what are the chances of something happenning if something else happens. The easiest example is this, what is the probablity that a family has 2 girls if they have 2 kids and one is girl? 1/3, because there are three combinations whith 2 kids and one girl (the sample size) and only one has 2 girls. another one of Bayes great laws is the law of large numbers or the golden theorem, " This law is the simplest law that was ever developed in probability" (121). As the book states it is pretty easy to understand, the larger the number of trials conducted the closer to the real mean you will get, and the more accurate you test will be. An example is this, if you flip a coin 10 times how many will be heads? how about if you flip it 1 million time? the second time the mean will be much closer to half of the number of trials. This effects everyday life and by simply applying this to other scenarios we can see that it really can help us out.
In the next chapter Mlodinow goes on to tell us the when he wrote a paper for his son's english class (who is in 10th grade and Mlodinow was editing but got carried away) only got a 93 he was infuriated. He then later learned that one of his colleaues (has a Phd in english and writes for the new york times) did the same thing but only got an 80%. Then two students turned in the same paper and one scored a 90% while the other only got a 79%(Mlodinow 136). How can this happen? We see that with thourough analyzation that when teachers grade numerous papers each day they get more tired and grade harder as they go on, or the grade later and get sloppier. So in fact your grades are all part of probability. But because of Bayes' golden theorem this is not true, as the more papers you write and get graded the closer to the true value of your work you will get. So grades have an amount of variance (atleast english grades) and this can change the scales roughly 10 % in either direction. He caries on to tell us that all measurements including human calculation contain error and there is alw to counter this error.