(Essay found in Nesselroade & Grimm, 2019; pgs. 596 – 597) Francis Galton (1822–1911) is credited with developing the concepts of correlation and regression, although his understudy, Karl Pearson, was responsible for many of the mathematical underpinnings of correlation. Galton led a full and varied life. Born into a wealthy English family, he was afforded the luxury of indulging his scientific curiosities. In the mid-1800s, European explorers were mapping the interior of Africa. Perhaps inspired by the travels of his prodigious cousin, Charles Darwin, Galton departed for Africa at the age of 28. His maps of unknown regions of Africa

(Essay found in Nesselroade & Grimm, 2019; pgs. 532 – 533) Karl Pearson was born in London in 1857, two years before Darwin published Origin of Species, a work that would shape Pearson’s entire academic life. It is reasonable to consider Pearson the father of modern statistics. Pearson completed the work on correlation that Galton had started, arriving at the coefficient that bears his name (the Pearson product-moment correlation). He subsequently devised formulas for computing correlations for variables that are noncontinuous (see Chapter 18). Pearson is responsible for many of the concepts and statistical terms that were introduced earlier in

(Essay found in Nesselroade & Grimm, 2019; pg. 404) John Tukey (1915–2000) was born in New Bedford, Massachusetts. He was homeschooled by his educator parents who responded to his numerous questions not with direct answers but with clues and follow-up questions designed to help him solve his own problems (McCullagh, 2003). This philosophy produced a remarkable student, culminating in two degrees from Brown University in Chemistry and a Ph.D. in mathematics from Princeton in 1939, where he was asked to stay-on as a professor upon graduation. He stayed at Princeton for his entire career. During World War II he decided

(Essay found in Nesselroade & Grimm, 2019; pgs. 379 – 380) Ronald Fisher (1890–1962) was born in England. He is considered a child prodigy. His daughter and biographer offers the following story. At about age three when he had been set up in his high chair for breakfast, he asked: “What is a half of a half?” His nurse answered that it was a quarter. After a pause, he asked, “And what’s a half of a quarter?” She told him that it was an eighth. There was a longer pause before he asked again, “What’s a half of an eighth,

(Essay found in Nesselroade & Grimm, 2019; pgs. 267-268) William Gosset (1876–1937) developed the t distribution as well as the independent- and dependent-samples t tests. After receiving a degree in chemistry and mathematics from Oxford, Gosset was hired by the Guinness brewery in Dublin in 1899. Around the turn of the century, many companies, especially in the agricultural industry, attempted to apply a scientific approach to product development. A typical research question would have been, “Which fertilizer will produce the largest corn yield?” or “What is the best temperature to brew ale so as to maximize its shelf life?” Until

(Essay found in Nesselroade & Grimm, 2019; pg. 186) Thomas Bayes (1701 – 1761) was a nonconformist (a term used for those who had problems with the Church of England) English cleric, statistician, and philosopher (Bellhouse, 2001). Although his interests were broad and his writings ranging from theology to a defense of Newton’s ideas regarding calculus, he is most well-known for a posthumously published paper by a friend in which he formulated a specific case of the theorem that now bears his name (Bayes’ Theorem; see section 6.9). His theorem solved the problem of inverse probability (also known as the,

(Essay found in Nesselroade & Grimm, 2019; pgs. 135-136) The discovery of the normal curve is usually attributed to Abraham De Moivre (1667 – 1754); being traced to a publication of his from 1733 (De Moivre, 1738; English Translation). He was a friend of people like Edmond Halley (of Halley’s Comet fame) and Sir Isaac Newton and was held in high esteem by the intellectual class of his time. Apparently, Newton occasionally replied to questions with, “Ask Mr. De Moivre, he knows all that better than I do” (Walker, 1934, p. 322). De Moivre’s discovery grew out of his interest

(Essay found in Nesselroade & Grimm, 2019; pgs. 39 – 40) Use the scale below to respond to the following statement: I enjoy studying statistics. ○ ○ ○ ○ ○ 1 2 3 4 5 Strongly Disagree Disagree Neither Disagree nor Agree Agree Strongly Agree If we have ever had to respond to a question in this manner, we can thank the social scientist, Rensis Likert. Likert, born in 1903 in Cheyenne, Wyoming, first began his undergraduate studies in 1922 in civil engineering, but then soon discovered that he preferred to study people instead of inanimate objects (Faculty History Project,

(Essay found in Nesselroade & Grimm, 2019; pg. 548) A common activity for many academic psychologists is the construction of measuring tools. There are literally hundreds of different psychological traits, tendencies, and abilities that psychologists are interested in measuring; from commonly used concepts like extroversion and neuroticism to less frequently-referenced concepts like humility (e.g., Rowatt et al., 2006) and right-wing authoritarianism (e.g., Mirels & Dean, 2006). The scales used to measure these attributes, however, need to be created. They do not appear out of thin air. Scale development is usually an extensive process.  First, the concept is carefully defined, with

(Essay found in Nesselroade & Grimm, 2019; pgs. 209- 210) Programs found on the internet allow us actually to see how changing the sample size, mean, and the standard deviation of the population of raw scores change the resulting sampling distribution. Some of the ones recently found online include the StatKey Sampling Distribution for a Proportion program (www.lock5stat.com/StatKey/sampling_1_cat/sampling_1_cat.html), the Rice Virtual Lab in Statistics (onlinestatbook.com/stat_sim/sampling_dist/) and the Rossman/Chance Applet Collection (www.rossmanchance.com/applets/OneSample.html). There are others. A program that is quite flexible, however, is one created by Dr. Patrick Wessa (www.wessa.net/rwasp_samplingdistributionmean.wasp). In this program, we can input the number of replications we