History of statistics and its significance

taradiddle of statistics and its significanceHistory of Statistics and its SignificanceStatistics is a relatively new subject, which branched from Probability Theory and is widely use in areas such as Economics and Astrology. It is a logic and methodology to measure scruple and it is used to do inferences on these uncertainties (Stigler, 1986). The history of Statistics can be starting linely traced back to the 1600s. John Graunt (1620-1674) could be considered as the pioneer of statistics and as the author of the first book regarding statistics. He published Natural and Political observations on the Bills of Mortality in 1662 whereby he was studying the plague outbreak in London at the time requested by the King. Graunt was asked to come up with a system that would allow them to detect threats of further outbreaks, by keeping records of mortality and causes of death and making an estimation of the population. By forming the behavior table, Graunt discovered that statistically, the ratio of male to females are almost equal. Then in 1666, he collected data and started to examine life expectancies. All of this was fundamental as he was arguably the first to occasion a condensed life table from large data and was able to do more or less analysis on it. In addition, this is widely used in life insurance today, showing the importance and significance of Graunts usage (Verduin, 2009). Another reason wherefore this is significant is because of his ability in demonstrating the value of data collection (Stigler, 1986). Then in 1693, Edmond Halley extended Graunts ideas and formed the first mortality table that statistically do the relationship between age and death rates. Again, this is used in life insurance (Verduin, 2009).Another contributor to the formation of statistics is Abraham De Moivre (1667-1823). He was the first person to discern the properties of the normal curve and in 1711, introduced the notion of statistical independence (Verduin, 2009). In 1724, De Moivre studied mortality statistics and laid down baseations of the theory of annuities, inspired by the work of Halley. This is significant as annuities are widely used in the Finance industry today, in particular, when forming actuarial tables in life insurance. De Moivre then went on to speech about the idea of the normal dissemination which can be used to approximate the binomial distribution (OConnor and Robertson, 2004).William Playfair (1759-1823) was the person who invented statistical chartics, which included the line chart and the bar graph chart in 1786 and the pie chart in 1801. He believed that charts were a better way to represent data and he was driven to this subterfuge by a lack of data. This was a milestone as these graphical representations are used everywhere today, the most notable being the time-series graph, which is a graph containing many data points measured at successive uniform intervals over a period of time. These graphs can be used to e xamine data such as shares, and could be used to predict future data (Robyn 1978).Adolphe Quetlet (1796-1874) was the first person to apply probability and statistics to Social Sciences in 1835. He was interested in studying about human characteristics and suggested that the law of errors, which are commonly used in Astronomy, could be applied when studying people and through this, assumptions or predictions could be in regards to physical features and intellectual features of a person. Through Quetlets studies, he discovered that the distribution of certain characteristics when he made a diagram of it was in a shape of a bell curve. This was a significant discovery as Quetlet later went on to form properties of the normal distribution curve, which is a vital excogitation in Statistics today. Using this concept of average man, Quetlet used this to examine other social issues such as crime rates and marriage rates. He is in addition well known for the coming up with a formula calle d the Quetlet Index, or more commonly known as Body Mass Index, which is an indication or measure for obesity. This is still used today and you could find out your BMI by calculating. If you get an index of more than 30, it means the person is officially obese (OConnor and Robertson, 2006). other members who made little but significance contributions to Statistics are Carl Gauss and Florence Nightingale. Gauss was the first person who played around with the least squares estimation method when he was interested in astronomy and attempted to predict the position of a planet. He later proved this method by assuming the errors are normally distributed. The method of least squares is widely used today, in Astronomy for example, in order to minimise the error and improve the accuracy of results or calculations (OConnor and Robertson, 1996). It was also the most commonly used method before 1827 when trying to combine inconsistent equations (Stigler, 1986). Nightingale was inspired by Quet lets work on statistical graphics and produced a chart detail the deaths of soldiers where she worked. She later went on to analyse that state and care of health check facilities in India. This was significant as Nightingale applied statistics to health problems and this led to the improvement of medical healthcare. Her important works were recognised as became the first female to be a member of the Royal Statistical Society (Cohen, 1984).One of the greatest contributors was Francis Galton (1822-1911) who helped create a statistical revolution which laid foundations for future statisticians like Karl Pearson and Charles Spearman (Stigler, 1986). He was related to Charles Darwin and had many interests, such as Eugenics and Anthropology. He came up with a identification number of vital concepts, including the regression, standard deviation and correlation, which came about when Galton was studying sweet peas. He discovered that the successive sweet peas were of different sizes but regressed towards the mean size and the distribution of their parents (Gavan Tredoux, 2007). He later went on to work with the idea of correlation when he was studying the heights of parents and the parents children when they reach adulthood, where he made a diagram of his findings and found an obvious correlation between the 2. He then performed a few other experiments and came to the conclusion that the index of the correlation was an indication to the degree in which the two variables were related to one another. His studies were significant as they are all fundamental in Statistics today and these methods are used in many areas for data analysis, specially with extracting meaningful information between different factors (OConnor and Robertson, 2003).The History of Statistics The Measurement of Uncertainty before 1900Stephen M StigelrPublisher Belknap Press of Harvard University Press, March 1, 1990p1, 4, 40, 266http//www.leidenuniv.nl/fsw/verduin/stathist/stathist.htmA short H istory of Probability and StatisticsKees Verduin goal Updated March 2009Last Accessed 02/04/2010http//www-history.mcs.st-and.ac.uk/Biographies/De_Moivre.htmlThe MacTutor History of maths archiveArticle by J J OConnor and E F RobertsonCopyright June 2004Last Accessed 05/04/2010The American Statistician Volume 32, No 1Quantitative graphics in statistics A brief historyJames R. Beniger and Dorothy L. Robynp1-11http//www-groups.dcs.st-andrews.ac.uk/history/Biographies/Quetelet.htmlThe MacTutor History of Mathematics archiveArticle by J J OConnor and E F RobertsonCopyright August 2006Last Accessed 06/04/2010http//www-history.mcs.st-and.ac.uk/Biographies/Gauss.htmlThe MacTutor History of Mathematics archiveArticle by J J OConnor and E F RobertsonCopyright December 1996Last Accessed 06/04/2010Scientific American 250Florence NightingaleI. Bernard CohenMarch 1984, p128-37/p98-107depending on country of salehttp//galton.org/Francis Galton edit and Maintained by Gavan TredouxLast Updated 12/1 1/07 (according to the update in News section)Last Accessed 07/04/2010http//www-history.mcs.st-and.ac.uk/Biographies/Galton.htmlThe MacTutor History of Mathematics archiveArticle by J J OConnor and E F RobertsonCopyright October 2003Last Accessed 07/04/2010