By David Etherton
A writer named Dale Carnegie once said, “Take a chance! All life is a chance. The man who goes farthest is generally the one who is willing to do and dare.” When you think about it, he is absolutely right. Everything we do in life is by chance. Whether you are starting a business or starting a rock band, running in a marathon or running for president, playing poker or playing slot machines, everything we do involves the chance that we may not succeed. It may be for this reason that a whole subfield of mathematics has been dedicated solely to chance; this subfield is known as probability theory.
Probability theory has existed for at least 350 years, although many believe that it has been around much longer than this (Burton, 2011, p. 439). This field originated from two different subjects: analyzing data to determine death & insurance rates (statistics), and how to win at games that are solely based on chance (probability) (Burton, 2011, p. 439).
To begin, the man who first laid the groundwork for the field of statistics was John Gaunt (Burton, 2011, p. 440). Gaunt, who worked as a merchant in London, was the earliest person to use a large set of data in making a set of statistics (Burton, 2011, p. 440). In 1662, he created a work that tried to categorize the causes of death among females and males in London (Burton, 2011, p. 440). When he saw that his work was not being utilized to its full potential, however, he decided to take matters into his own hands (Burton, 2011, p. 440). To put his work to good use, Gaunt collected over 50 years of data, in fact, and then analyzed it to see the mortality rates for people at different ages (Burton, 2011, p. 440).
Now, for the field of probability, we need to go a little bit further back in time. It is said that people started playing games of chance (gambling) over 5000 years ago, and that the first dice were invented around 3000 BC in Iraq (Burton, 2011, p. 443). The invention of playing cards is a little bit hazy, as it is said that the Chinese, Egyptians, and Indians may have all created it (Burton, 2011, p. 444). Much later on during in the 16th century, a man by the name of Girolamo Cardan wrote a book called Liber de Ludo Aleae, which not only defined probability, but was also the first source to relate probability to games of chance (Burton, 2011, p. 445). It is not Cardan, however, who is said to have revolutionized probability theory. In 1654, a man named Chevalier de Méré was concerned with questions of gambling, so he sent his inquiries to Blaise Pascal (Burton, 2011, p. 454). Pascal, in turn, wrote Pierre de Fermat to help him with these problems (Burton, 2011, p. 454). They worked together on the probability involved in throwing dice and, as a result of their combined efforts, these two people are known to have developed probability theory (Burton, 2011, p. 455).
After all these years, probability and statistics hold a fine place in mathematics, and in my opinion, it is because there are many so different ways to apply this topic to the real world, and, over the years, probability and statistics have evolved quite a bit and are now the focus of many careers. An example of one of these careers would be an actuary, who gets paid to determine how much risk is involved in various situations, how much money could be lost or made during these situations. Another example would be statisticians (big surprise, right?), which collect data and analyze it by various means. There are many careers that revolve around probability and statistics, and one thing worth mentioning about many of these jobs is that they can pay very well. According to the Bureau of Labor Statistics (2009), actuaries made a median salary of over $84,000 in the year of 2008, and some actually made over $160,000. The Bureau of Labor Statistics (2009) also states that statisticians were making a median salary of about $72,000 in 2008, with some easily breaking the six-figure mark.
For more information about what these types of careers entail, you may want to visit the following websites.
http://www.amstat.org/careers/
http://www.beanactuary.org/
Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2010-11 Edition, Actuaries, on the Internet at http://www.bls.gov/oco/ocos041.htm (visited November 10, 2011).
Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2010-11 Edition, Statisticians, on the Internet at http://www.bls.gov/oco/ocos045.htm (visited November 10, 2011).
Burton, D. M. (2011). The development of probability theory: Pascal, Bernoulli, and Laplace. In
The history of mathematics (Seventh ed., pp. 439-496). New York, NY: McGraw-Hill. (Original work published 1999)
Chance quotes. (n.d.). Retrieved from http://www.brainyquote.com/quotes/keywords/chance_2.html
A writer named Dale Carnegie once said, “Take a chance! All life is a chance. The man who goes farthest is generally the one who is willing to do and dare.” When you think about it, he is absolutely right. Everything we do in life is by chance. Whether you are starting a business or starting a rock band, running in a marathon or running for president, playing poker or playing slot machines, everything we do involves the chance that we may not succeed. It may be for this reason that a whole subfield of mathematics has been dedicated solely to chance; this subfield is known as probability theory.
Probability theory has existed for at least 350 years, although many believe that it has been around much longer than this (Burton, 2011, p. 439). This field originated from two different subjects: analyzing data to determine death & insurance rates (statistics), and how to win at games that are solely based on chance (probability) (Burton, 2011, p. 439).
To begin, the man who first laid the groundwork for the field of statistics was John Gaunt (Burton, 2011, p. 440). Gaunt, who worked as a merchant in London, was the earliest person to use a large set of data in making a set of statistics (Burton, 2011, p. 440). In 1662, he created a work that tried to categorize the causes of death among females and males in London (Burton, 2011, p. 440). When he saw that his work was not being utilized to its full potential, however, he decided to take matters into his own hands (Burton, 2011, p. 440). To put his work to good use, Gaunt collected over 50 years of data, in fact, and then analyzed it to see the mortality rates for people at different ages (Burton, 2011, p. 440).
Now, for the field of probability, we need to go a little bit further back in time. It is said that people started playing games of chance (gambling) over 5000 years ago, and that the first dice were invented around 3000 BC in Iraq (Burton, 2011, p. 443). The invention of playing cards is a little bit hazy, as it is said that the Chinese, Egyptians, and Indians may have all created it (Burton, 2011, p. 444). Much later on during in the 16th century, a man by the name of Girolamo Cardan wrote a book called Liber de Ludo Aleae, which not only defined probability, but was also the first source to relate probability to games of chance (Burton, 2011, p. 445). It is not Cardan, however, who is said to have revolutionized probability theory. In 1654, a man named Chevalier de Méré was concerned with questions of gambling, so he sent his inquiries to Blaise Pascal (Burton, 2011, p. 454). Pascal, in turn, wrote Pierre de Fermat to help him with these problems (Burton, 2011, p. 454). They worked together on the probability involved in throwing dice and, as a result of their combined efforts, these two people are known to have developed probability theory (Burton, 2011, p. 455).
After all these years, probability and statistics hold a fine place in mathematics, and in my opinion, it is because there are many so different ways to apply this topic to the real world, and, over the years, probability and statistics have evolved quite a bit and are now the focus of many careers. An example of one of these careers would be an actuary, who gets paid to determine how much risk is involved in various situations, how much money could be lost or made during these situations. Another example would be statisticians (big surprise, right?), which collect data and analyze it by various means. There are many careers that revolve around probability and statistics, and one thing worth mentioning about many of these jobs is that they can pay very well. According to the Bureau of Labor Statistics (2009), actuaries made a median salary of over $84,000 in the year of 2008, and some actually made over $160,000. The Bureau of Labor Statistics (2009) also states that statisticians were making a median salary of about $72,000 in 2008, with some easily breaking the six-figure mark.
For more information about what these types of careers entail, you may want to visit the following websites.
http://www.amstat.org/careers/
http://www.beanactuary.org/
Bibliography
Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2010-11 Edition, Actuaries, on the Internet at http://www.bls.gov/oco/ocos041.htm (visited November 10, 2011).
Bureau of Labor Statistics, U.S. Department of Labor, Occupational Outlook Handbook, 2010-11 Edition, Statisticians, on the Internet at http://www.bls.gov/oco/ocos045.htm (visited November 10, 2011).
Burton, D. M. (2011). The development of probability theory: Pascal, Bernoulli, and Laplace. In
The history of mathematics (Seventh ed., pp. 439-496). New York, NY: McGraw-Hill. (Original work published 1999)
Chance quotes. (n.d.). Retrieved from http://www.brainyquote.com/quotes/keywords/chance_2.html
This article shows that there are many different opportunities for mathematicians. I have always known that there was a job called an actuary but this article explained to me what the job of a actuary is. When I read this article it helped me to think of many idea for my mathematics classes. Students want to understand what the reason is behind them learning topics in mathematics classes. When students can see that this could be their future career they will begin to listen and comprehend the mathematical topics of probability and statistics.
ReplyDelete~Miranda
this is actually a very nice introduction to cost benefit analysis in economics. which use the methods of both probability and statistics to determine if running a marathon has more benefits than the time effort and costs associated with running long distances. one way to evaluate the examples that you have mentioned above would be to use pay off tables (matrices) to evaluate whether or not these options are worth doing or in gambling whether or not the conditions allow for a favorable outcome. oddly enough another career option that hires mathematicians for prob and stats work is casinos and video game developers. Overall this information was very useful and insightful.
ReplyDelete~Josh
I was blown away at how well this article was written. Not only was it informative as to the types of jobs that mathematics can offer, but the history of probability. I did not know that dice were invented some 5ooo years ago! I spent the last 3 and a half years of my life in Nevada and never gambled; however, I watched many who did and lost their money quickly. I could imagine how a casino would pay top dollar to an statistician or actuary in order to make profit at whatever it costs. As I read the article I wondered if such jobs were also used to create games with low success rates or games with high success rates to keep people interested in gambling. It would be interesting to find out! Great read.
ReplyDeleteSpencer
First off, let me begin by saying that maybe I have chosen the wrong career. Maybe I should pursue the career of an actuarie, they make bank! Anyways back to the blog, I found this blog to be very interesting because I can relate to a lot of this key information because I am in Probability and Statistics I right now. We do a lot of analyzing data and calculating probability. However I do have a question. Does probability theory relate at all to Chaos Theory? Chaos theory deals somewhat with the likeliness of random events and trying to make order out of it, so that is what sparked that question for me. Also, I was surprised to see that Pascal was involved with the origination of probability theory because I knew some information about his already, but not this. All in all, great article David!
ReplyDeleteI look forward to taking statistics because I have a feeling that I will enjoy it. I have considered a career in the field of actuary. There's a definite need for them, as this career is steadily expanding. It's interesting to see how big of a role mathematics plays out in real-life day to day situations. This is quite informative and motivates me to look more into careers that are very math involved.
ReplyDelete