Answer: Use mnemonics.
Here’s a list of over 3000 handy mnemonics:
Practical Savvy Solutions to Everyday Problems
thousands of proven, simple ways you can change your life for the better
Professor Eric Cassell, eminent medical ethicist and internist, talking about the importance of treating a person, not a patient:
http://www.youtube.com/watch?v=_rVhanPxepU&feature=related
On the importance of mastering rescue from failure:
How do we heal medicine?
Advice to surgeons and doctors in general:
Update on how to improve balance and reduce falls
William James
Erich Fromm
Peter Drucker
John Maynard Keynes
Margaret Mead
Albert Ellis
Ellen Langer
Carol Dweck
Others
The remarkable collaborative friendship between psychologists Daniel Kahneman and Amos Tversky is a beautiful example of what is possible.
From 1968 to 1969, I taught a graduate seminar on the applications of psychology to real-world problems. In what turned out to be a life-changing event, I asked my younger colleague Amos Tversky to tell the class about what was going on in his field of judgment and decision-making. Amos told us about the work of his former mentor, Ward Edwards, whose lab was using a research paradigm in which the subject is shown two bookbags filled with poker chips. The bags are said to differ in their composition (e.g., 70:30 or 30:70 white/red). One of them is randomly chosen, and the participant is given an opportunity to sample successively from it, and required to indicate after each trial the probability that it came from the predominantly red bag. Edwards had concluded from the results that people are “conservative Bayesians”: they almost always adjust their confidence interval in the proper direction, but rarely far enough. A lively discussion developed around Amos’s talk. The idea that people were conservative Bayesian did not seem to fit with the everyday observation of people commonly jumping to conclusions. It also appeared unlikely that the results obtained in the sequential sampling paradigm would extend to the situation, arguably more typical, in which sample evidence is delivered all at once. Finally, the label of ‘conservative Bayesian’ suggested the implausible image of a process that gets the correct answer, then adulterates it with a bias. I learned recently that one of Amos’s friends met him that day and heard about our conversation, which Amos described as having severely shaken his faith in the neo-Bayesian idea. I do remember that Amos and I decided to meet for lunch to discuss our hunches about the manner in which probabilities are “really” judged. There we exchanged personal accounts of our own recurrent errors of judgment in this domain, and decided to study the statistical intuitions of experts.
I spent the summer of 1969 doing research at the Applied Psychological Research Unit in Cambridge, England. Amos stopped there for a few days on his way to the United States. I had drafted a questionnaire on intuitions about sampling variability and statistical power, which was based largely on my personal experiences of incorrect research planning and unsuccessful replications. The questionnaire consisted of a set of questions, each of which could stand on its own – this was to be another attempt to do psychology with single questions. Amos went off and administered the questionnaire to participants at a meeting of the Mathematical Psychology Association, and a few weeks later we met in Jerusalem to look at the results and write a paper.
The experience was magical. I had enjoyed collaborative work before, but this was something different. Amos was often described by people who knew him as the smartest person they knew. He was also very funny, with an endless supply of jokes appropriate to every nuance of a situation. In his presence, I became funny as well, and the result was that we could spend hours of solid work in continuous mirth. The paper we wrote was deliberately humorous – we described a prevalent belief in the “law of small numbers,” according to which the law of large numbers extends to small numbers as well. Although we never wrote another humorous paper, we continued to find amusement in our work – I have probably shared more than half of the laughs of my life with Amos.
And we were not just having fun. I quickly discovered that Amos had a remedy for everything I found difficult about writing. No wet-mush problem for him: he had an uncanny sense of direction. With him, movement was always forward. Progress might be slow, but each of the myriad of successive drafts that we produced was an improvement – this was not something I could take for granted when working on my own. Amos’s work was always characterized by confidence and by a crisp elegance, and it was a joy to find those characteristics now attached to my ideas as well. As we were writing our first paper, I was conscious of how much better it was than the more hesitant piece I would have written by myself. I don’t know exactly what it was that Amos found to like in our collaboration – we were not in the habit of trading compliments -but clearly he was also having a good time. We were a team, and we remained in that mode for well over a decade. The Nobel Prize was awarded for work that we produced during that period of intense collaboration.
At the beginning of our collaboration, we quickly established a rhythm that we maintained during all our years together. Amos was a night person, and I was a morning person. This made it natural for us to meet for lunch and a long afternoon together, and still have time to do our separate things. We spent hours each day, just talking. When Amos’s first son Oren, then fifteen months old, was told that his father was at work, he volunteered the comment “Aba talk Danny.” We were not only working, of course – we talked of everything under the sun, and got to know each other’s mind almost as well as our own. We could (and often did) finish each other’s sentences and complete the joke that the other had wanted to tell, but somehow we also kept surprising each other.
We did almost all the work on our joint projects while physically together, including the drafting of questionnaires and papers. And we avoided any explicit division of labor. Our principle was to discuss every disagreement until it had been resolved to mutual satisfaction, and we had tie-breaking rules for only two topics: whether or not an item should be included in the list of references (Amos had the casting vote), and who should resolve any issue of English grammar (my dominion). We did not initially have a concept of a senior author. We tossed a coin to determine the order of authorship of our first paper, and alternated from then on until the pattern of our collaboration changed in the 1980s.
One consequence of this mode of work was that all our ideas were jointly owned. Our interactions were so frequent and so intense that there was never much point in distinguishing between the discussions that primed an idea, the act of uttering it, and the subsequent elaboration of it. I believe that many scholars have had the experience of discovering that they had expressed (sometimes even published) an idea long before they really understood its significance. It takes time to appreciate and develop a new thought. Some of the greatest joys of our collaboration-and probably much of its success – came from our ability to elaborate each other’s nascent thoughts: if I expressed a half-formed idea, I knew that Amos would be there to understand it, probably more clearly than I did, and that if it had merit he would see it. Like most people, I am somewhat cautious about exposing tentative thoughts to others – I must first make sure that they are not idiotic. In the best years of the collaboration, this caution was completely absent. The mutual trust and the complete lack of defensiveness that we achieved were particularly remarkable because both of us – Amos even more than I – were known to be severe critics. Our magic worked only when we were by ourselves. We soon learned that joint collaboration with any third party should be avoided, because we became competitive in a threesome.
Amos and I shared the wonder of together owning a goose that could lay golden eggs – a joint mind that was better than our separate minds. The statistical record confirms that our joint work was superior, or at least more influential, than the work we did individually (Laibson and Zeckhauser, 1998). Amos and I published eight journal articles during our peak years (1971-1981), of which five had been cited more than a thousand times by the end of 2002. Of our separate works, which in total number about 200, only Amos’ theory of similarity (Tversky, 1977) and my book on attention (Kahneman, 1973) exceeded that threshold. The special style of our collaborative work was recognized early by a referee of our first theoretical paper (on representativeness), who caused it to be rejected by Psychological Review. The eminent psychologist who wrote that review – his anonymity was betrayed years later – pointed out that he was familiar with the separate lines of work that Amos and I had been pursuing, and considered both quite respectable. However, he added the unusual remark that we seemed to bring out the worst in each other, and certainly should not collaborate. He found most objectionable our method of using multiple single questions as evidence – and he was quite wrong there as well.
Alas, the close, collaborative friendship was unable to last. Kahneman wrote:
Anne Treisman and I married and moved together to U.B.C. in 1978, and Amos and Barbara Tversky settled in Stanford that year. Amos and I were then at the peak of our joint game, and completely committed to our collaboration. For a few years, we managed to maintain it, by spending every second weekend together and by placing multiple phone calls each day, some lasting several hours. We completed the study of framing in that mode, as well as a study of the ‘conjunction fallacy’ in judgment (Tversky and Kahneman, 1983). But eventually the goose that had laid the golden eggs languished, and our collaboration tapered off. Although this outcome now appears inevitable, it came as a painful surprise to us. We had completely failed to appreciate how critically our successful interaction had depended on our being together at the birth of every significant idea, on our rejection of any formal division of labor, and on the infinite patience that became a luxury when we could meet only periodically. We struggled for years to revive the magic we had lost, but in vain.We were again trying when Amos died. When he learned in the early months of 1996 that he had only a few months to live, we decided to edit a joint book on decision-making that would cover some of the progress that had been made since we had started working together on the topic more than twenty years before (Kahneman and Tversky, 2000). We planned an ambitious preface as a joint project, but I think we both knew from the beginning that we would not be granted enough time to complete it. The preface I wrote alone was probably my most painful writing experience.
Kahneman wrote a beautiful eulogy to Amos Tversky, with this touching ending:
Much of the joy was social. Almost all of Amos’ work was collaborative. He enjoyed working with colleagues and students, and he was supremely good at it. And his joy was infectious. The 12 or 13 years in which most of our work was joint were years of interpersonal and intellectual bliss. Everything was interesting, almost everything was funny, and there was the recurrent joy of seeing an idea take shape. So many times in those years we shared the magical experience of one of us saying something which the other would understand more deeply than the speaker had done. Contrary to the old laws of information theory, it was common for us to find that more information was received than had been sent. I have almost never had that experience with anyone else. If you have not had it, you don’t know how marvelous collaboration can be …
Over 10 million copies of The Elements of Style have been sold in its various editions. The 1918 original edition was a slim 45-page book written in William Strunk’s delightfully dogmatic style. It hasn’t been out of print since.
Here’s the pdf version of the original 1918 version. Print it off and study Strunk’s wise advice. Maybe some of his advice on word usage is now out of date, but it’s still a remarkable collection of writing wisdom that is just a click away:
Or, better still, buy the latest version: the 105-page, 1999 fourth edition of The Elements of Style by William Strunk Jr. and E.B White.
The Anticreativity Letters: Advice from a Senior Tempter to a Junior Tempter
Reference: Nisbett, R. E. (1990). The anti-creativity letters: Advice from a senior tempter to a junior tempter. American Psychologist, 45, 1078-1082.
The Anticreativity Letters is eminent psychologist Richard Nesbitt’s clever take on C. S. Lewis’s The Screwtape Letters for psychologists.
Written in the form of letters, The Anticreativity Letters is a letter correspondence between senior devil, Snidely, and junior devil, Slump. All of the letters are from Snidely to Slump, and the subject of the correspondence is a budding academic research psychologist, whom Snidely calls “the patient.” Snidely is advising Slump in the wily skills of how to lead the patient away from a career of creative productivity towards a career of drab mediocrity or out of the academic profession altogether.
1. Stay away from sneery, critical colleagues who dismiss your ideas who are always too eager to as “old hat”, trivial and unworkable:
“. . .you want to steer him away from the people who are absorbed in interesting work, and toward the sneerers. When it comes to associates, there is nothing so useful as sneerers, especially if they are intelligent and witty. They are sure to dismiss your patient’s ideas, should he be so foolish as to discuss them, as trivial, old hat, obvious, or patently ridiculous. Old hat is really the most useful accusation because it need never be proved. The clever sneerer knows that he or she need merely assert that an idea is an old one. Such an assertion will not be called into question one time in a hundred. . . My colleague Fallow very nearly succeeded in throwing Leon Festinger off the trail of dissonance theory by encouraging him to associate with people who could be counted on to tell him that dissonance was nothing more than rationalization recycled into new bottles. Festinger’s unfortunate self-confidence blocked that move, but with a more humble patient you would have won every time. . .
. . .Each member of the faculty could find six flaws in every design, 12 artifactual explanations for every finding, and 24 predecessors for every alleged original idea. Every student adopted that same stance toward his or her fellows. And, most important, that critical stance became part of the scientific conscience of every student. As a result, hardly one of those talented students has lived up to the early promise shown. Each of them can be counted on to shoot on sight any glimmer of an idea the moment it makes an appearance on the horizon of the mind.”
2. Read widely and cultivate an interesting group of friends. You never know where your next good idea will come from:
“I note you have steered him away from philosophy and literature by intimations of “hot air,” “speculation,” “fantasy,” “waste of time,” and so forth. This is much to be commended because great philosophy and great literature are an unparalleled source of ideas in psychology. . .
. . .Few things are more calculated to destroy creativity. Whatever original ideas he might have will slowly become assimilated to what he is reading, so that his work will be at best derivative. Unless he is very energetic, in fact, he can be counted on to give up research altogether on the grounds that he never has any ideas that someone else didn’t already have. . .
It is particularly important to prevent him from talking with his colleagues. A cup of coffee with a stimulating colleague can be a disaster. It can easily result in a new idea, a new perspective, a new career! And yet it is so easily avoided. Busy, busy. Not today. Nose to the grindstone.”
3. Don’t isolate yourself. Work closely with your supervisor and colleagues. Talk about your ideas with others:
“Nearly all young graduate students in the social sciences think that learning how to do research is like learning how to write a novel. That is, they think they have to come up with an idea, which they then work on more or less in solitude, with occasional criticism and advice from a professional. That, after all, is the way they functioned with their senior honors theses. (It never occurs to them that custodial care is all that most faculty are willing to give to undergraduates engaged in research.) So they don’t realize that a continuation of that apparently grown-up way of functioning will keep them largely ignorant of how to pursue an idea across a series of investigations, in the face of failure, criticism, and a host of unanticipated difficulties.
We know, of course, that learning how to do research is really like learning how to make movies. There are many things to be learned that are quite invisible to the novice, some highly technical, some grand strategic, and some mundane-seeming but crucial. The only way to do this is by working shoulder to shoulder, trustingly, with someone who already knows how to do it.”
4. Don’t agonize over your perceived lack of intelligence or creativity or social standing of your research field:
“All but the very most brilliant patients are therefore candidates for constant worry about whether they are smart enough to succeed. . .
Remember that such people literally have more to lose than to gain by producing something. They know this, and live in constant fear of doing work that is unworthy of them. No idea, of course, however important, seems obviously valuable or even very sensible in its formative stages. The minute a famously smart young person has an idea, you want to encourage speculation about whether it is really earth shaking if true or really true if earth shaking. . . Give me a patient with an IQ of 170 and I’ll produce mental paralysis by the age of 30 more often than not.
But worries about creativity are the best. Regardless of your patient’s real or ascribed intelligence, he is bound to have doubts about his creativity. It is hard to believe, but humans actually think there is a property of creativity that one can either “have” or “not have,” as opposed to a talent for some field–a love of its content that keeps them thinking about it all the time–organization, and a willingness to work. . .
It is important to remember how social scientists view the Great Chain of Being. They think that sociologists are on the bottom and mathematicians are on the top. A consequence is that the psychologists are always trying to impress the biologists, the biologists the chemists, and the chemists the physicists. This makes most psychologists into rabid reductionists. They think this is good scientific strategy, but it is really just biologist envy.”
5. Don’t jump on to whatever is trendy. Think up your own research ideas:
“What is troubling about your patient is that the research is something that he is genuinely interested in, something that proceeds from long-time concerns and that builds both on the thinking and the research skills that he developed in his research with his major adviser. What you want is to have him working on some trendy topic he has picked up by reading the journals. You want him to see some piece of moderately interesting work, get him to thinking that it is ridden with alternative explanations, and have him redo the experiments with the major purpose of showing that he is cleverer than the original investigators. Research is least dangerous when it is most reactive.”
6. Focus on quality rather than quantity of output:
“There is a direct analogy here for the relation between creativity and sheer production for the modern professional, especially scientific professionals. They know that what counts is creativity and that all creative people are productive in some sense. They also know that it can be hard to tell just what work is genuinely creative. From there it is only a step to get them to focus exclusively on the productivity and to slide into a tacit equation of productivity and creativity. Here you have the academic reward structure massively on your side. Academic decision makers count notably better than they read. We have recently encouraged the rapid promotion and advancement of many psychologists whose work, whatever its value in terms of quality, is wretchedly excessive in terms of numbers of publications.”
7. Don’t get caught up in time-wasting chores:
“. . .even if he is obsessed with work, he can’t do research continually. What you want to do is make any other work he does as barren for him as possible. Get him to take the same driven stance toward preparing his courses that he does toward his research. Put him into an endless round of overpreparing his lectures and tracking down minutiae that won’t interest his students in the least. When this is done right, little research is accomplished, the teaching gets steadily worse, and the patient is a bitter, burnt-out case by the time he is denied tenure. . .
. . .It is important to remember that teaching in moderation is actually valuable for research. The necessity of explaining one’s concerns to others, and of putting them into a broader context, together with the effort to demonstrate why certain topics are interesting, all have the most direct benefits for thinking about research. We have had great success with scientists at the modern research institutes who are relieved of all need for teaching. Most of them are turning out to cease all productive activity within a matter of a few years after arrival.”
8. Live a balanced life. Invest time into forming close, satisfying relationships with others:
“I think you are quite mistaken to cackle over the fact that your patient has fallen in love. It is true that love affords innumerable distractions and that he will be quite incapable of work during the inevitable troughs in the relationship. But on balance we have more to lose than we have to gain. Freud pointed out that the primary concerns . . .are love and work. When a human’s love life is going well, work is likely to be carried out with special joy and contentment. These emotions are our deadly enemy.
You may claim that it is mere coincidence, but it is certainly the case that your patient is doing suspiciously interesting work lately.”
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1. Elliot Aronson: eminent social psychologist, author of best seller The Social Animal and the only person in the 120-year history of the American Psychological Association to win all three of its major awards for distinguished research, distinguished teaching, and distinguished writing.
Elliot Aronson is the only person in the 120-year history of the American Psychological Association to win all three of its major awards for distinguished research, distinguished teaching, and distinguished writing.
In the last 10 minutes of the 30-minute video below, Elliot Aronson talks about how he wrote his journal articles and books on social psychology. Move the time cursor to 19′ 30″:
Watch these 85+ brilliant videos on various topics in introductory statistics by Salman Khan from the Khan Academy.
If you don’t know about the Khan Academy, the free online website with over 3300 instructional videos that have been downloaded over 175 million times, then watch this TED video and be impressed:
from the Khan Academy website:
Statistics
Introduction to statistics. Will eventually cover all of the major topics in a first-year statistics course (not there yet!)Videos
- Mean Median and Mode
- Range and Mid-range
- Reading Pictographs
- Reading Bar Graphs
- u08_l1_t2_we2 Reading Line Graphs
- Reading Pie Graphs (Circle Graphs)
- Misleading Line Graphs
- u08_l1_t2_we3 Stem-and-leaf Plots
- Box-and-Whisker Plots
- Reading Box-and-Whisker Plots
- Statistics: The Average
- Statistics: Sample vs. Population Mean
- Statistics: Variance of a Population
- Statistics: Sample Variance
- Statistics: Standard Deviation
- Statistics: Alternate Variance Formulas
- Introduction to Random Variables
- Probability Density Functions
- Binomial Distribution 1
- Binomial Distribution 2
- Binomial Distribution 3
- Binomial Distribution 4
- Expected Value: E(X)
- Expected Value of Binomial Distribution
- Poisson Process 1
- Poisson Process 2
- Law of Large Numbers
- Normal Distribution Excel Exercise
- Introduction to the Normal Distribution
- ck12.org Normal Distribution Problems: Qualitative sense of normal distributions
- ck12.org Normal Distribution Problems: z-score
- ck12.org Normal Distribution Problems: Empirical Rule
- ck12.org Exercise: Standard Normal Distribution and the Empirical Rule
- ck12.org: More Empirical Rule and Z-score practice
- Central Limit Theorem
- Sampling Distribution of the Sample Mean
- Sampling Distribution of the Sample Mean 2
- Standard Error of the Mean
- Sampling Distribution Example Problem
- Confidence Interval 1
- Mean and Variance of Bernoulli Distribution Example
- Bernoulli Distribution Mean and Variance Formulas
- Margin of Error 1
- Margin of Error 2
- Confidence Interval Example
- Small Sample Size Confidence Intervals
- Hypothesis Testing and P-values
- One-Tailed and Two-Tailed Tests
- Z-statistics vs. T-statistics
- Type 1 Errors
- Small Sample Hypothesis Test
- T-Statistic Confidence Interval
- Large Sample Proportion Hypothesis Testing
- Variance of Differences of Random Variables
- Difference of Sample Means Distribution
- Confidence Interval of Difference of Means
- Clarification of Confidence Interval of Difference of Means
- Hypothesis Test for Difference of Means
- Comparing Population Proportions 1
- Comparing Population Proportions 2
- Hypothesis Test Comparing Population Proportions
- Squared Error of Regression Line
- Proof (Part 1) Minimizing Squared Error to Regression Line
- Proof (Part 3) Minimizing Squared Error to Regression Line
- Proof (Part 4) Minimizing Squared Error to Regression Line
- Regression Line Example
- Proof Part 2 Minimizing Squared Error to Line
- R-Squared or Coefficient of Determination
- Second Regression Example
- Calculating R-Squared
- Covariance and the Regression Line
- Chi-Square Distribution Introduction
- Pearson’s Chi Square Test (Goodness of Fit)
- Contingency Table Chi-Square Test
- ANOVA 1 – Calculating SST (Total Sum of Squares)
- ANOVA 2 – Calculating SSW and SSB (Total Sum of Squares Within and Between).avi
- ANOVA 3 -Hypothesis Test with F-Statistic
- Correlation and Causality
- Deductive Reasoning 1
- Deductive Reasoning 2
- Deductive Reasoning 3
- U12_L1_T3_we1 Inductive Reasoning 1
- Inductive Reasoning 2
- Inductive Reasoning 3
- U03_L1_T1_we2 Inductive
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