Here are 100 books that A Student's Guide to Open Science fans have personally recommended if you like
A Student's Guide to Open Science.
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I am the Fletcher Jones Professor of Economics at Pomona College. I started out as a macroeconomist but, early on, discovered stats and stocks—which have long been fertile fields for data torturing and data mining. My book, Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics is a compilation of a variety of dubious and misleading statistical practices. More recently, I have written several books on AI, which has a long history of overpromising and underdelivering because it is essentially data mining on steroids. No matter how loudly statisticians shout correlation is not causation, some will not hear.
Ritchie was part of a team that attempted to replicate a famous study led by a prominent psychologist, Daryl Bem, claiming that people did better on a word memorization test if they studied the words after taking the test.
Ritchie and his co-authors attempted to replicate this study and found no evidence supporting Bem’s claim. This is but one example of a scientific crisis in that attempts to replicate influential studies published in top peer-reviewed journals fail nearly half the time. Ritchie explains and illustrates the reasons for the current replication crisis in science.
An insider’s view of science reveals why many scientific results cannot be relied upon – and how the system can be reformed.
Science is how we understand the world. Yet failures in peer review and mistakes in statistics have rendered a shocking number of scientific studies useless – or, worse, badly misleading. Such errors have distorted our knowledge in fields as wide-ranging as medicine, physics, nutrition, education, genetics, economics, and the search for extraterrestrial life. As Science Fictions makes clear, the current system of research funding and publication not only fails to safeguard us from blunders but actively encourages bad…
Magical realism meets the magic of Christmas in this mix of Jewish, New Testament, and Santa stories–all reenacted in an urban psychiatric hospital!
On locked ward 5C4, Josh, a patient with many similarities to Jesus, is hospitalized concurrently with Nick, a patient with many similarities to Santa. The two argue…
I gradually shifted my statistics teaching from significance testing — traditional but bamboozling — to estimation (confidence intervals), which I called "the new statistics" because, although not new, relying on it would, for many researchers, be very new. It’s more informative, makes sense, and is a pleasure to teach and use. I "retired" to write Understanding the New Statistics. Then Open Science arrived—hooray! Robert Calin-Jageman joined me for an intro textbook with Open Science and The New Statistics all through. Our first edition came out in 2017. The second edition has wonderful new open-source software (‘esci’), which is also ideal for more advanced students and researchers. Enjoy!
You may have heard of ‘significance testing,’ and the magical ‘p < .05,’ which somehow makes a research result ‘significant,’ which is often taken as (almost) ‘true.’ Even if you haven’t heard of all that, Kline explains clearly why significance testing has been disastrous for science, leading to misleading conclusions and much valuable research not even being reported.
He draws on my work to explain how ‘the new statistics’ (estimation) is a much better way to understand results. The first chapter is fairly easy to read. Later chapters are also terrific but get more technical as Kline explains lots of ways to do things better. As I’m quoted on the back cover, “Read this book and see the future!” Happily, the future is increasingly looking as Kline recommended.
Traditional education in statistics that emphasises significance testing leaves researchers and students ill prepared to understand what their results really mean. Specifically, most researchers and students who do not have strong quantitative backgrounds have difficulty understanding outcomes of statistical tests.
As more and more people become aware of this problem, the emphasis on statistical significance in the reporting of results is declining. Increasingly, researchers are expected to describe the magnitudes and precisions of their findings and also their practical, theoretical, or clinical significance.
This accessibly written book reviews the controversy about significance testing, which has now crossed various disciplines as…
I gradually shifted my statistics teaching from significance testing — traditional but bamboozling — to estimation (confidence intervals), which I called "the new statistics" because, although not new, relying on it would, for many researchers, be very new. It’s more informative, makes sense, and is a pleasure to teach and use. I "retired" to write Understanding the New Statistics. Then Open Science arrived—hooray! Robert Calin-Jageman joined me for an intro textbook with Open Science and The New Statistics all through. Our first edition came out in 2017. The second edition has wonderful new open-source software (‘esci’), which is also ideal for more advanced students and researchers. Enjoy!
Yes, this is a textbook, but if you are seeking a research design and methods text for psychology or a related discipline, this is easily my top choice.
There are lots of references to topical stories to keep everything relevant for students. There’s a truckload of valuable stuff online to support both teachers and learners. This fourth edition is right up-to-the-moment, Chapter 3 especially so, as it explains three types of scientific claims, and four types of validity that researchers should aim to achieve. That may sound forbidding, but Morling’s examples and explanations are pleasingly accessible.
Featuring an emphasis on future consumers of psychological research and examples drawn from popular media, Research Methods in Psychology: Evaluating a World of Information develops students' critical-thinking skills as they evaluate information in their everyday lives. The Fourth Edition of this best-selling text takes learning to a new level for both consumers and producers by offering new content, interactive learning, and online assessment to help them master the concepts.
Former model Kira McGovern picks up the paint brushes of her youth and through an unexpected epiphany she decides to mix ashes of the deceased with her paints to produce tributes for grieving families.
Unexpectedly this leads to visions and images of the subjects of her work and terrifying changes…
I gradually shifted my statistics teaching from significance testing — traditional but bamboozling — to estimation (confidence intervals), which I called "the new statistics" because, although not new, relying on it would, for many researchers, be very new. It’s more informative, makes sense, and is a pleasure to teach and use. I "retired" to write Understanding the New Statistics. Then Open Science arrived—hooray! Robert Calin-Jageman joined me for an intro textbook with Open Science and The New Statistics all through. Our first edition came out in 2017. The second edition has wonderful new open-source software (‘esci’), which is also ideal for more advanced students and researchers. Enjoy!
Another research design textbook, this one more specifically about neuroscience. My co-author, neuroscientist Robert Calin-Jageman, highly recommends it.
This third edition has clear and up-to-date discussions of issues such as phacking and publication bias that emphasise the need for Open Science. There’s a focus on effect sizes and confidence intervals, as in the new statistics. The book also describes strategies needed to enhance the rigor and reproducibility of neuroscience research.
Using engaging prose, Mary E. Harrington introduces neuroscience students to the principles of scientific research including selecting a topic, designing an experiment, analyzing data, and presenting research. This new third edition updates and clarifies the book's wealth of examples while maintaining the clear and effective practical advice of the previous editions. New and expanded topics in this edition include techniques such as optogenetics and conditional transgenes as well as a discussion of rigor and reproducibility in neuroscience research. Extended coverage of descriptive and inferential statistics arms readers with the analytical tools needed to interpret data. Throughout, practical guidelines are provided…
I’ve always loved unreliable narrators and how they place us as readers into the role of detectives, piecing the "truth" of a story together. The narrators I’ve picked below vary in their intent: some deliberately deceive, and others do so unconsciously or through omission. In several, the twist hinges on the use of an unreliable narrator, while in others, narrative unreliability poses a moral dilemma for the reader. In a few, an added layer of unreliability emerges: the narrator’s perception is distorted by technology. In an age of AI, simulations, and deep fakes, the unreliable narrator is arguably more needed than ever, holding a mirror up to the unreliability of our own world.
I find it interesting when first-person unreliable narrators pose a moral dilemma for the reader: how far we sympathise with a character who may or may not be culpable of a crime.
From the very opening of the novel, we are told, "Tonight will be my first night under house arrest." Ruth Ardingly has just been released from prison to serve out a sentence of house arrest for arson and suspected murder (after the death of her seven-year-old grandson) at her farm, The Well. Returning to The Well, Ruth must piece together the tragedy that shattered her marriage and tore her family apart, amid the backdrop of a drought-ridden country, where, miraculously, The Well has water.
The novel is told retrospectively by Grandmother Ruth, whose narrative reliability is impacted by both memory and grief.
AN OBSERVER NEW FACE OF FICTION 2015 A HUFFINGTON POST 'ONE TO WATCH IN 2015'
LONGLISTED FOR THE CWA JOHN CREASEY (NEW BLOOD) DAGGER 2015
'I was gripped by Catherine Chanter's The Well immediately. The beauty of her prose is riveting, the imagery so assured. This is an astonishing debut' Sarah Winman, author of When God was a Rabbit
'I loved this book!' JESSIE BURTON, author of The Miniaturist
When Ruth Ardingly and her family first drive up from London in their grime-encrusted car and view The Well, they are enchanted by a…
I am proud to be a human (social) scientist but think that we could collectively achieve a much more successful human science enterprise. And I believe that a better human science would translate into better public policy. Most human scientists focus on their own research, paying little attention to how the broader enterprise functions. I have written many works of a methodological nature over the years. I am pleased to point here to a handful of works with sound advice for enhancing the human science enterprise.
Though this book focuses on psychology, it has lessons for all social sciences.
Chambers, like me, is critical of certain practices and yet deeply respectful of what has been accomplished. He devotes much of his attention to the problem of confirmation bias. We as humans are more likely to accept results that conform to prior beliefs.
Journals are also more likely to publish such results. Scholars play with their findings, adding or removing data points to achieve a target level of statistical significance. The result is that we are often more confident in scholarly consensus than we should be. Chambers explains complex ideas clearly, and is passionate about the need for reform.
Why psychology is in peril as a scientific discipline-and how to save it
Psychological science has made extraordinary discoveries about the human mind, but can we trust everything its practitioners are telling us? In recent years, it has become increasingly apparent that a lot of research in psychology is based on weak evidence, questionable practices, and sometimes even fraud. The Seven Deadly Sins of Psychology diagnoses the ills besetting the discipline today and proposes sensible, practical solutions to ensure that it remains a legitimate and reliable science in the years ahead. In this unflinchingly candid manifesto, Chris Chambers shows how…
Rusty Allen is an Iraqi War veteran with PTSD. He moves to his grandfather's cabin in the mountains to find some peace and go back to wilderness training.
He gets wrapped up in a kidnapping first, as a suspect and then as a guide. He tolerates the sheriff's deputy with…
While growing up as a budding intellectual, two of my passions were social science (in other words, politics), and natural science, particularly biology. For decades, I thought of those as two unconnected fields of knowledge. I studied politics in my professional capacity as a government professor, and I read nature and wildlife studies as a hobby. Then, one day in 2000, I picked up a copy of a book by Stephen J. Gould, a Harvard paleontologist. It struck me that in every sentence he was combining science and politics. It was an on-the-road-to-Damascus moment. Since then, I have studied and written about the politics of evolution.
A Marxist critique of evolutionary biology, authored by a geneticist, a neuroscientist, and a psychologist. From a perspective about as far from the viewpoint of creationists as it is possible to get, these three scholars argue that the philosophical assumptions, methodology, and social organization of modern biology add up to a politically conservative conspiracy reinforcing capitalism, racism, classism, and misogyny. Although their attack is general, it is most specifically aimed at intelligence testing, which, they argue, is shoddy science in the service of racist ideology.
Not in our Genes systematically exposes and dismantles the claims that inequalities class, race, gender are the products of biological, genetic inheritances. 'Informative, entertaining, lucid, forceful, frequently witty... never dull... should be read and remembered for a long time.' - New York Times Book Review. 'The authors argue persuasively that biological explanations for why we act as we do are based on faulty (in some cases, fabricated) data and wild speculation... It is debunking at its best.' - Psychology Today
I am a historian and author, passionate about how the past influences current ideas and perceptions. While reading for my Ph.D. in Historical Theory, I started to realise that it is not the past that influences us, but we that actually create it. The books in the list came up at different points in my life and research and made me think and rethink the concept of historical knowledge, how we acquire it, how we narrate it, and what we retain from it.
When I first read this book as a history student, it just blew my mind.
Keith Jenkins is an expert at criticizing the roots of historiography in the clearest but also most hilarious way. I learned so much about understanding historical texts and was excited by Jenkin’s urge to move historical thinking beyond narratives of good and evil.
Main lesson learned: Don’t take things too seriously, especially if they already happened!
"Why bother with history? Keith Jenkins has an answer. He helps us re-think the "end of history", as signalled by postmodernity. Readers may disagree with him, but he never fails to provoke debate about the future of the past."
Joanna Bourke, Professor of History, Birkbeck College
Keith Jenkins' work on historical theory is renowned; this collection presents the essential elements of his work over the last fifteen years.
Here we see Jenkins address the difficult and complex question of defining the limits of history. The collection draws together the key pieces of his work in one handy volume, encompassing the…
I am passionate about bringing back to life persons from the past who have been forgotten, misunderstood, or even deliberately mischaracterized. In order to get to the truth, there are a host of myths that must be shattered or discarded. Most of the histories that I have written have done precisely this–showing the fallacy of familiar myths and discovering the hidden truths about people and events that have been distorted, often by some of the most popular literature. In order to achieve these results, I have had to spend years in “boring” archives in order to reveal people and events that are never boring.
When I recommended this book to a petroleum geologist, he later told me that it was probably the best book he had ever read–and he understood for the first time what historians actually do (and parenthetically, why the closest field to history in methodology is, in fact, geology).
I’ve also seen undergraduate students come alive intellectually by reading these lectures, given at Oxford by Gaddis as a visiting professor. They are full of remarkable insights into everything from human psychology to fractal geometry. Every chapter is an intellectual feast, showing the vast variety of the historian’s sources and methods.
What is history and why should we study it? Is there such a thing as historical truth? Is history a science? One of the most accomplished historians at work today, John Lewis Gaddis, answers these and other questions in this short, witty, and humane book. The Landscape of History provides a searching look at the historian's craft, as well as a strong argument for why a historical consciousness should matter to us today. Gaddis points out that while the historical method is more sophisticated than most historians realize, it doesn't require unintelligible prose to explain. Like cartographers mapping landscapes, historians…
Portrait of an Artist as a Young Woman
by
Alexis Krasilovsky,
Kate from Jules et Jim meets I Love Dick.
A young woman filmmaker’s journey of self-discovery, set against a backdrop of the sexual liberation movement of the 1970s and 1980s. In Portrait of an Artist as a Young Woman, we follow Ana Fried as she faces the ultimate…
As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!
This book, by Nate Silver of 538 fame, explains in a straightforward manner why so many predictions by “experts,” from weather forecasts to sports outcomes to election polling to economics, ultimately prove wrong.
It relates to understanding the “signal,” the underlying science that is often revealed through trends and patterns in data, relative to the “noise,” the random or unpredictable variations always present in data. Silver also explains the concept of conditional probability, probability when provided with some relevant information, in an unusually clear manner.
The book reads more like a casual conversation with the author, rather than a statistics textbook.
UPDATED FOR 2020 WITH A NEW PREFACE BY NATE SILVER
"One of the more momentous books of the decade." —The New York Times Book Review
Nate Silver built an innovative system for predicting baseball performance, predicted the 2008 election within a hair’s breadth, and became a national sensation as a blogger—all by the time he was thirty. He solidified his standing as the nation's foremost political forecaster with his near perfect prediction of the 2012 election. Silver is the founder and editor in chief of the website FiveThirtyEight.
Drawing on his own groundbreaking work, Silver examines the world of prediction,…