Trick or Treatment: The Undeniable Facts About Alternative Medicine
by Edzard Ernst and Simon Singh · 17 Aug 2008 · 357pp · 110,072 words
illustrates particularly well how an evidence-based approach forces the medical establishment to accept the conclusions that emerge when medicine is put to the test. Florence Nightingale, the Lady with the Lamp, was a woman with very little reputation, but she still managed to win a bitter argument against the male-dominated
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Naples. Then Florence was born in the spring of 1820, and she too was named after the city of her birth. It was expected that Florence Nightingale would grow up to live the life of a privileged English Victorian lady, but as a teenager she regularly claimed to hear God’s voice
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, she also drew multicoloured diagrams that would not look out of place in a modern boardroom presentation. She even invented an elaborate version of the pie chart, known as the polar area chart, which helped to illustrate her data. She realized that illustrating her statistics would be enormously helpful in selling her
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system of collecting medical records. In turn, this resulted in a careful monitoring of which conditions and treatments did and did not benefit patients. Today, Florence Nightingale is best known as the founder of modern nursing, having established a curriculum and training college for nurses. However, it can be argued that her
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young lives: ‘You might as well take 1,100 men every year out upon Salisbury Plain and shoot them.’ The lesson to be learned from Florence Nightingale’s medical triumphs is that scientific testing is not just the best way to establish truth in medicine, but it is also the best mechanism
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triumphant when we analyse the data concerning its efficacy. After all, these alternative therapists can probably identify with the mavericks that have populated this chapter. Florence Nightingale would have been perceived as a maverick during her early career, because she was prioritizing hygiene when everybody else involved in healthcare was focused on
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book. Anita and Danielle have shared our joys and our anxieties, our hopes and our fears. Thank you. Picture Credits James Lind © Wellcome Library, London Florence Nightingale’s polar chart © Wellcome Library, London Model showing acupuncture needle entry points © Wellcome Library, London Patient receiving acupuncture © Tek Image/Science Photo Library Archie Cochrane
The Data Detective: Ten Easy Rules to Make Sense of Statistics
by Tim Harford · 2 Feb 2021 · 428pp · 103,544 words
of making the same statistical mistakes that we’ve always made—only prettier. • Michael Blastland, co-creator of BBC Radio 4’s More or Less Florence Nightingale would have needed no introduction in Victorian Britain: she was the nation’s unofficial patron saint, and was the only nonroyal woman to appear on
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this day; the 4,000-bed London hospital constructed in a few days to meet the demands of the pandemic was named Nightingale Hospital. In Florence Nightingale’s own time, the only woman more recognizable would have been Queen Victoria herself. The nation revered Nightingale for her “feminine” heroics in the Crimean
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sense of it. But many of us who are dazzled by infographics don’t suspect a thing. * * * — All that lay far in the future when Florence Nightingale was a girl discovering a passion for data. At the age of nine she was categorizing and graphing the plants in her garden. As she
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and Quetelet were later to be founders of the Royal Statistical Society; Nightingale, as I have mentioned, became its first female fellow. By her thirties, Florence Nightingale was steeped in this world of pioneering mathematicians—but her job was as nursing superintendent at a small hospital in London’s Harley Street, where
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. Reports in The Times turned the Crimean War into a long-running narrative of disaster with many familiar characters. By the end of it all, Florence Nightingale was perhaps the only figure to retain public support; the generals and the rest had been discredited by the catastrophe. The Barrack Hospital in Scutari
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book, without well-defined standards for statistical record-keeping, nothing adds up. Numbers can easily confuse us when they are unmoored from a clear definition. Florence Nightingale may have been a savvy campaigner, but her campaigns were built on the most solid of foundations. * * * — The most straightforward problem with a clever decorative
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time to think a little harder. If we don’t, we’re allowing ourselves to be dazzled. * * * — The situation in the Scutari hospital was catastrophic. Florence Nightingale was later to write, “To inexperienced eyes the Scutari buildings were magnificent. To ours, in their first state, they were truly whited sepulchers, pest houses
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make the hospital less unpleasant, but the immediate effect was to cut the death rate almost immediately from more than 50 percent to 20 percent. Florence Nightingale wanted to understand what had happened, and why. And like Richard Doll and Austin Bradford Hill, she believed she could work out the truth if
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deaths. Nightingale set herself the task of proving him wrong. William Farr’s daughter, Mary, described eavesdropping on an early conversation between her father and Florence Nightingale. Mary recalled Farr giving Nightingale a warning about speaking out against the establishment. “‘Well, if you do it, you will make yourself enemies,’ and she
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kind of comparison. That, in turn, suggests a particular choice of graph—such as a scatterplot, a line graph, a stacked bar chart, or a pie chart.* Finally, underline your message by sticking it in the graph title. Don’t just write “Number of contracts, January–August.” Write something like “The number
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your tone of voice can dramatically alter how your words will be received.19 * * * — How could a lowborn statistician, William Farr, and a mere female, Florence Nightingale, win over the stubborn doctors and soldiers of the Victorian establishment? First, they had to make sure their data were absolutely watertight. Facta, facta! Farr
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diseases before and after the sanitary improvements at Scutari. If you wanted to be unkind about the diagram, you could say that it is a pie chart on steroids. Technically, it’s a polar area diagram, quite possibly the first such diagram ever created. What it isn’t is a dry presentation
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sanitation. In the 1870s, Parliament passed several public health acts. Death rates in the UK began to fall, and life expectancy to rise. What makes Florence Nightingale’s story so striking is that she was able to see that statistics could be tools and weapons at the same time. She appreciated the
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need to give the data a makeover, presenting them in the most persuasive light. She produced a picture with enough power to change the world. Florence Nightingale was on the right side of history, but many of the people who misuse catchy graphics are not. For those of us on the receiving
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1. For more information about the life and statistical contribution of Florence Nightingale, see Mark Bostridge, Florence Nightingale: The Woman and Her Legend (New York: Penguin, 2009); Lynn McDonald, ed., The Collected Works of Florence Nightingale (Waterloo, ON: Wilfrid Laurier University Press, 2009–10), and “Florence Nightingale: Passionate Statistician,” Journal of Holistic Nursing 28, no. 1 (March 2010
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); Hugh Small, “Did Nightingale’s ‘Rose Diagram’ Save Millions of Lives?,” seminar paper, Royal Statistical Society, October 7, 2010; I. Bernard Cohen, “Florence Nightingale,” Scientific American 250, no
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. 3 (1984), 128–37, JSTOR, www.jstor.org/stable/24969329; Eileen Magnello, “Florence Nightingale: A Victorian Statistician,” Mathematics in School, May 2010, and “The Statistical Thinking and Ideas of
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Florence Nightingale and Victorian Politicians,” Radical Statistics, issue 102. 2. Draft from John Sutherland (presumed on behalf of Florence Nightingale) to William Farr, March 1861. 3. These quotes from Nightingale are in Marion Diamond and Mervyn Stone, “Nightingale on Quetelet
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/11/23/lessons-from-posting-a-fake-map/#5138b31959ec. 11. Florence Nightingale, “Notes on the Health of the British Army,” in McDonald, The Collected Works of Florence Nightingale, vol. 14, 37. 12. See McDonald, The Collected Works of Florence Nightingale, vol. 14, 551–52. 13. Letter from Florence Nightingale to Sidney Herbert, August 19, 1857. 14. Alberto Cairo
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28, 2016, https://www.infoworld.com/article/3088166/why-how-to-lie-with-statistics-did-us-a-disservice.html. 20. Letter from William Farr to Florence Nightingale, November 24, 1863, quoted in John M. Eyler, Victorian Social Medicine: The Ideas and Methods of William Farr (London: Johns Hopkins University Press, 1979), 175
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. 21. Science Museum, “Florence Nightingale: The Pioneer Statistician,” December 10, 2018, https://www.sciencemuseum.org.uk/objects-and-stories/florence-nightingale-pioneer-statistician. Rule Ten: Keep an Open Mind 1. Leon Festinger, Henry Riecken, and Stanley Schachter, When Prophecy
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of data, 237. See also open-mindedness; visualization of data Peters, Tom, 123 Phillips curve, 218n photos as data, 62–64 physics research, 244–47 pie charts, 224, 228, 233–34 Pierson, Emma, 177 Piketty, Thomas, 83 Pinker, Steven, 71–72, 96–97 placebo, 53, 125–26, 130 Planck’s constant, 246
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notice something. As a 2006 economics paper observed, “Japan’s Phillips curve looks like Japan.” *The Big Issue put Florence Nightingale on its cover in March 2020. “Hail the Hand-Washing Queen: How Florence Nightingale Is Helping Us Fight Coronavirus,” the magazine trumpeted. But it takes more than handwashing to power a revolution in
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fighting a pandemic requires information, as quick and as complete as possible. Florence Nightingale understood that nearly two hundred years ago. I’d rather remember her not as a handwashing queen, but as a data detective. *Joking. Don’t use a pie chart. *In an act of sweet revenge, Hill later showed how to
Keeping Up With the Quants: Your Guide to Understanding and Using Analytics
by Thomas H. Davenport and Jinho Kim · 10 Jun 2013 · 204pp · 58,565 words
’s a simple “here’s what happened” analytical story. This type of story can almost always be described in simple graphical terms—a bar chart, pie chart, graph, or something more visually ambitious, such as an interactive display. There are some people who prefer rows and columns of numbers over more visually
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, can successfully convince the intended audience or completely undermine the importance of those results. Let’s look at an example of each. Florence Nightingale: A Good Example of Communicating Results Florence Nightingale is widely known as the founder of the profession of nursing and a reformer of hospital sanitation methods, but she was also
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-1). While taken for granted now, it was at that time a relatively novel method of presenting data. Her innovative diagrams were a kind of pie chart with displays in the shape of wedge cuts. Nightingale printed them in several colors to clearly show how the mortality from each cause changed from
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returned to England in June of 1856 after the Crimean War ended, she found herself a celebrity and praised as a heroine. FIGURE 4-1 * * * Florence Nightingale’s diagram of the causes of mortality in the “Army in the East” The Areas of the blue, red, & black wedges are each measured from
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their sexiness. However, visual analytics (also known as data visualization) have advanced dramatically over the last several years. If you’re just using bar and pie charts, you’re only scratching the surface of what you can do with visual display. “Purposes and Types of Visual Analytics” may not include all of
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multiple variables; can also show change in multiple categories with different colors See the parts of a whole and how they relate to each other: Pie chart: Displays distribution of values in one variable in a pie format; percentages of each value correspond to size of slices Tree map: Visual for showing
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=246428. 4. I. Bernard Cohen, The Triumph of Numbers: How Counting Shaped Modern Life (New York: W.W. Norton, 2006), chapter 9; “Florence Nightingale,” Wikipedia, http://en.wikipedia.org/wiki/Florence_Nightingale; P. Nuttall, “The Passionate Statistician,” Nursing Times 28 (1983): 25–27. 5. Gregor Mendel, “Experiments in Plant Hybridization,” http://www.mendelweb.org
Statistics in a Nutshell
by Sarah Boslaugh · 10 Nov 2012
discusses outliers. Some of the most commonly used graphical techniques for presenting statistical information are also covered in this chapter, including frequency tables, bar charts, pie charts, Pareto charts, stem and leaf plots, boxplots, histograms, scatterplots, and line graphs. Chapter 5, Categorical Data Reviews the concepts of categorical and interval data and
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years). It is immediately clear that the proportion of underweight students has declined, and the proportion of overweight and obese students has increased over time. Pie Charts The familiar pie chart presents data in a manner similar to the stacked bar chart: it shows graphically what proportion each part occupies of the whole
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. Pie charts, like stacked bar charts, are most useful when there are only a few categories of information and the differences among those categories are fairly large.
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Many people have particularly strong opinions about pie charts, and although pie charts are still commonly used in some fields, they have also been aggressively denounced in others as uninformative at best and potentially misleading at worst
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. So you must make your own decision based on context and convention; I will present the same BMI information in pie chart form (Figure 4-30), and you may be the judge of whether this is a useful way to present the data. Note that this is
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sections (to show a more detailed breakdown of categories within a segment). Figure 4-30. Pie chart showing BMI distribution for freshmen entering in 2005 Florence Nightingale and Statistical Graphics Most people are at least vaguely familiar with Florence Nightingale’s role in establishing nursing as a profession and with her heroic efforts to improve hygiene
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the Internet along with a discussion of her accomplishments in this field. One example is Julie Rehmeyer’s Science News article from November 26, 2008, “Florence Nightingale: The Passionate Statistician”. Pareto Charts The Pareto chart or Pareto diagram combines the properties of a bar chart and a line chart; the bars display
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of majors, the less frequent majors might be combined for the sake of clarity). Problem One of the following data sets is appropriate for a pie chart, and one is not. Identify which is which, and explain why. Influenza cases for the past two years, broken down by month The number of
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causes for absenteeism at a hospital (the fifth category is “all other,” including all absences attributed to causes other than the first four) Solution A pie chart would not be a good choice for the influenza data set because it would have too many categories (24), many of the categories are probably
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a bar chart or line chart showing the number of cases by month or season. The absenteeism data would be a good candidate for a pie chart because there are only five categories, and the parts do add up to 100% of a whole. One question that can’t be answered from
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(or slices of the pie) are clearly of different size; if so, that would be a further argument in favor of the use of a pie chart. Problem What is the median of this data set? 8 3 2 7 6 9 1 2 1 Solution 3. The data set has 9
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regression models, Methods for Building Regression Models, Backward removal–Backward removal balance, in research design structure, Ingredients of a Good Design bar charts, Bar Charts–Pie Charts Bartlett test, Unequal Variance t-Test, Factor Analysis baseline response variable, Specifying Response Variables Bayes, Thomas, Bayes’ Theorem Bayes’ theorem (formula), Bayes’ Theorem–Bayes’ Theorem
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and Interquartile Range, The Variance and Standard Deviation–The Variance and Standard Deviation, Outliers–Outliers, Graphic Methods–Frequency Tables, Frequency Tables–Frequency Tables, Bar Charts–Pie Charts, Pie Charts, Pareto Charts–Pareto Charts, The Stem-and-Leaf Plot, The Boxplot–The Boxplot, The Histogram–Bivariate Charts, Bivariate Charts, Scatterplots–Scatterplots, Line Graphs–Line Graphs
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, Descriptive Statistics and Graphic Displays critiquing an article, Descriptive Statistics–Extrapolation and Trends graphical methods, Graphic Methods–Frequency Tables, Frequency Tables–Frequency Tables, Bar Charts–Pie Charts, Pie Charts, Pareto Charts–Pareto Charts, The Stem-and-Leaf Plot, The Boxplot–The Boxplot, The Histogram–Bivariate Charts, Bivariate Charts, Scatterplots–Scatterplots, Line Graphs–Line Graphs
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, Scatterplots–Relationships Between Continuous Variables about, Graphic Methods–Frequency Tables bar charts, Bar Charts–Pie Charts bivariate charts, Bivariate Charts boxplot, The Boxplot–The Boxplot frequency tables, Frequency Tables–Frequency Tables histogram, The Histogram–Bivariate Charts line graphs, Line Graphs–Line
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Graphs Pareto charts, Pareto Charts–Pareto Charts pie charts, Pie Charts scatterplots, Scatterplots–Scatterplots, Scatterplots–Relationships Between Continuous Variables stem-and-leaf plot, The Stem-and-Leaf Plot interpretation of, Descriptive Statistics–Extrapolation and Trends measures
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, The t Distribution Graduate Record Examination (GRE), Factor Analysis graphical methods, Graphic Methods–Frequency Tables, Graphic Methods–Frequency Tables, Frequency Tables–Frequency Tables, Bar Charts–Pie Charts, Pie Charts, Pareto Charts–Pareto Charts, The Stem-and-Leaf Plot, The Boxplot–The Boxplot, The Histogram–Bivariate Charts, Bivariate Charts, Scatterplots–Scatterplots, Line Graphs–Line Graphs
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, Scatterplots–Relationships Between Continuous Variables about, Graphic Methods–Frequency Tables, Graphic Methods–Frequency Tables bar charts, Bar Charts–Pie Charts bivariate charts, Bivariate Charts, Scatterplots–Scatterplots, Line Graphs–Line Graphs, Scatterplots–Relationships Between Continuous Variables about, Bivariate Charts line graphs, Line Graphs–Line Graphs scatterplots
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Between Continuous Variables boxplot, The Boxplot–The Boxplot frequency tables, Frequency Tables–Frequency Tables histogram, The Histogram–Bivariate Charts Pareto charts, Pareto Charts–Pareto Charts pie charts, Pie Charts stem-and-leaf plot, The Stem-and-Leaf Plot graphical power calculator, Power Analysis graphical presentation of data, critiquing in articles, Graphical Presentation of Data
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of Roots negative discrimination, Item Analysis Nelson quality control rules, Run Charts and Control Charts Nelson, Lloyd S., Run Charts and Control Charts Nightingale, Florence, Pie Charts NIST/SEMATECH e-Handbook of Statistical Methods (National Institute of Standards and Technology (U.S.)), Probability Tables for Common Distributions NNT (Number Needed to Treat
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, Permutations, and Combinations permutations of elements, Permutations phi coefficient, Binary Variables–Binary Variables, Item Analysis physical vs. social sciences, definition of treatments, Specifying Treatment Levels pie charts, Pie Charts placebo, Glossary of Statistical Terms placebo effect, Blinding, Glossary of Statistical Terms playing cards, Dice, Coins, and Playing Cards point estimates, calculating, Confidence Intervals point
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, The Boxplot rectangular data file in, The Rectangular Data File, The Rectangular Data File SRS (Simple Random Sampling), Probability Sampling stacked bar chart, Bar Charts–Pie Charts standard deviation, The Normal Distribution–The Normal Distribution, The Variance and Standard Deviation–The Variance and Standard Deviation, The Variance and Standard Deviation, The Variance
The Formula: How Algorithms Solve All Our Problems-And Create More
by Luke Dormehl · 4 Nov 2014 · 268pp · 75,850 words
a rolling history of your sex life on which to reflect.”31 This mass of data can be visualized in a variety of forms—including pie charts and scatter plots—with heat maps showing different intensities of color based on the quantity and quality of sex a particular user is having. “The
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for being of “substantial interest and importance.” Charles Darwin read Quetelet’s work, as did Fyodor Dostoyevsky (twice), while no less a social reformer than Florence Nightingale based her statistical methods upon his own.13 Nightingale later gushingly credited Quetelet’s findings with “teaching us . . . the laws by which our Moral Progress
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). 13 Mlodinow, Leonard. The Drunkard’s Walk: How Randomness Rules Our Lives (New York: Pantheon Books, 2008). 14 Belt, Elmer, and Louise Darling. Elmer Belt Florence Nightingale Collection (San Francisco: Internet Archive, 2009). 15 Danzigera, Shai, Jonathan Levav and Liora Avnaim-Pesso. “Extraneous Factors in Judicial Decisions.” PNAS, vol. 108, no. 17
The Data Journalism Handbook
by Jonathan Gray, Lucy Chambers and Liliana Bounegru · 9 May 2012
was much higher than official numbers showed. Figure 1-9. Data journalism in the Guardian in 1821 (the Guardian) Another early example in Europe is Florence Nightingale and her key report, “Mortality of the British Army”, published in 1858. In her report to Parliament, she used graphics to advocate improvements in health
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month, which highlighted that the vast majority of deaths were from preventable diseases rather than bullets. Figure 1-10. Mortality of the British army by Florence Nightingale (image from Wikipedia) Data Journalism and Computer-Assisted Reporting At the moment there is a “continuity and change” debate going on around the label “data
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chart to clearly show the import and export quantities of Scotland in a new and visual way. He then went on to popularize the dreaded pie chart in his 1801 book Statistical Breviary. The need for these new forms of charts and graphs came out of commerce, but as time passed, others
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/google-d-s/spreadsheets/. Figure 6-21. UK government spending and taxation (the Guardian) After something simple (like a bar or line chart, or a pie chart), you’ll find that Google spreadsheets (which you create from the documents bit of your Google account) can create some pretty nice charts—including the