DATA, DECISIONS, UNCERTAINTY A HISTORY Kevin S. Robinson, PhD krobinson@millersville

1. DATA, DECISIONS, UNCERTAINTY A HISTORY Kevin S. Robinson, PhD krobinson@millersville.edu

2. Girolamo Cardano lived from 1501 to 1576, Italy Cool Fact: consulted by Leonardo da Vinci on questions of geometry In addition to Cardano's major contributions to algebra he also made important contributions to probability, hydrodynamics, mechanics and geology. His book Liber de Ludo Aleae was published in 1663 but the book on games of chance was probably completed by 1563. Cardano makes the first ever foray into the, until then untouched, realm of probability theory. It is the first study of things such as dice rolling, based on the premise that there are fundamental scientific principles governing the likelihood of achieving the elusive 'double six', outside of mere luck or chance.

3. The Unfinished Game: Pascal, Fermat, and the Seventeenth-Century Letter that Made the World Modern In the early seventeenth century, the outcome of something as simple as a dice roll was consigned to the realm of unknowable chance. Mathematicians largely agreed that it was impossible to predict the probability of an occurrence. Then, in 1654, Blaise Pascal wrote to Pierre de Fermat explaining that he had discovered how to calculate risk. The two collaborated to develop what is now known as probability theory; a concept that allows us to think rationally about decisions and events.

4. Jacob Bernoulli - 1654 to 1705 - Swiss Cool Fact: Jacob had always found the properties of the logarithmic spiral to be almost magical and he had requested that it be carved on his tombstone with the Latin inscription Eadem Mutata Resurgo meaning "I shall arise the same though changed". By 1689 he had published important work on infinite series and published his law of large numbers in probability theory. The interpretation of probability as relative-frequency says that if an experiment is repeated a large number of times then the relative frequency with which an event occurs equals the probability of the event. The law of large numbers is a mathematical interpretation of this result.

5. Normal Distribution (1808) Carl Friedrich Gauss & Pierre-Simon Laplace A very readable article about the Normal Distribution: http://tinyurl.com/normal-ksr Misconception: Something is “wrong” if the distribution is non-normal ... Often, distributions other than the normal are more appropriate for a given set of data. Normality is a myth; there never has, and never will be, a normal distribution. Roy C. Geary (1896 - 1983) Roy C. Geary was undoubtedly the most eminent Irish statistician and economist of the twentieth century.

6. Francis Galton - 1822 to 1911 - English one of the most exceptional statisticians of his time his scientific achievements were substantial and his influence on statistics is still felt strongly today. Galton introduced many important statistical concepts that are now standard in many statistical analyses; including correlation, regression and percentiles. Cool Fact: Galton's career bore remarkable similarities to that of his cousin Charles Darwin. Like Darwin, Galton attended Cambridge, but did not do exceptionally well. He spent a period of traveling before settling down to scientific work. And like Darwin, Galton had caught hold of the controversial ideas, which he realized could only be adequately proved by careful scientific investigation (Forrest, 1995). Galton placed an extremely high value upon science.

7. Karl Pearson - 1857 to 1936 – English Galton’s statistical heir – Pearson a major player in the early development of statistics as a serious scientific discipline in its own right. He founded the Department of Applied Statistics (now the Department of Statistical Science) at University College London in 1911; it was the first university statistics department in the world. He had become interested in the idea that sound mathematics could be applied to natural phenomena not only under the category of causation, but also under the broader category of correlation, and had in 1893 contributed his first statistical paper to the Royal Society, of which he was elected a Fellow in 1896. Whatever his other distinctions, he will be most widely known to posterity as the inspirer and largely the creator of a body of statistical theory concerning frequency curves, correlation, goodness of fit, etc., most of which has appeared in Biometrika, begun in 1901 after the Royal Society had "resolved that mathematics and biology should not be mixed," as he himself phrased it.

8. William Gosset - 1876 to 1937 - English He invented the t-test (1908) to handle small samples for quality control in brewing. He discovered the form of the t distribution by a combination of mathematical and empirical work with random numbers, an early application of the Monte-Carlo method. -- under a pseudonym ("Student") To many in the statistical world "Student" was regarded as a statistical advisor to Guinness's brewery, to others he appeared to be a brewer devoting his spare time to statistics. There is some truth in both these ideas but miss the central point, which was the intimate connection between his statistical research and the practical problems on which he was engaged.

9. Sir Ronald Aylmer Fisher - 1890 to 1962 - English a genius who almost single-handedly created the foundations for modern statistical science & the greatest biologist since Darwin … important contributions to statistics, include the analysis of variance (ANOVA), method of maximum likelihood, experimental design. Cool Fact: Fisher had poor eyesight, which made reading difficult; so he learned through listening to others read aloud to him. He started out studying mathematics (and excelling at it) but began to focus on statistics because of his interest in evolutionary theory.

10. John Tukey - 1915 to 2000 - American one of the most influential statisticians of the last 50 years and a wide-ranging thinker …  spent decades as both a professor at Princeton University and a researcher at AT&T's Bell Laboratories. In 1970, Tukey published ''Exploratory Data Analysis,'' which gave new ways to analyze and present data clearly – tools include, the stem-and-leaf display and boxplot which continue in high school and higher-ed curriculums. The best thing about being a statistician is that you get to play in everyone's backyard. Tukey believed that, after the first 40 years, the practitioners of statistics lost sight of its original objectives of finding methods of analyzing data that described patterns, trends, and relationships, and detected anomalies. In 1962, he maintained that mathematical statistics was ignoring real-world data analysis. He urged a return to the origins of scientific statistics, using modern methods in which the statistical description of the data was paramount. Cool Fact: In 1944, Tukey coined the term "bit," an abbreviation of "binary digit", to describe the 1s and 0s that are the basis of the binary code in which all digital computer programs are produced. He was also credited with conceiving the word "software".

11. Hal Ronald Varian (born March 18, 1947, in Wooster, Ohio) is an economist specializing in microeconomics and information economics. He is the chief economist at Google and he holds the title of emeritus professor at the University of California, Berkeley where he was founding dean of the School of Information. I keep saying the sexy job in the next ten years will be statisticians. People think I'm joking, but -- the ability to take data - to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it's going to be a hugely important skill in the next decades, not only at the professional level but even at the educational level for elementary school kids, for high school kids, for college kids. Because now we really do have essentially free and ubiquitous data. So the complimentary scarce factor is the ability to understand that data …

12. Statistics is a general intellectual method that applies wherever data, variation, and chance appear. It is a fundamental method because data, variation, and chance are omnipresent in modern life. However, working with data is an art as well as a science. We learn it not simply by mastering formal methods but by following examples set by our current teachers and by past masters. In this, learning statistics is like learning to perform music, another subject in which students develop practical wisdom and critical evaluation through context and example. We learn in this way because technique alone does not make an outstanding statistician any more than an out-standing musician. Interpretation in the specific context is always important. Technology is not enough … technology empowers but thinking enables … Reading Arithmetic Writing Think Show Tell Recognition Computation Interpretation