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Precognition paper to be published in mainstream journal

 In one experiment, students were shown a list of words and then asked to recall words from it, after which they were told to type words that were randomly selected from the same list. Spookily, the students were better at recalling words that they would later type.
Spooky my a**. All they've said there is that a student has shown they remembered a word and then when asked to type some words later that is one of the ones the typed. Would you believe it.
 In another study, Bem adapted research on "priming" – the effect of a subliminally presented word on a person's response to an image. For instance, if someone is momentarily flashed the word "ugly", it will take them longer to decide that a picture of a kitten is pleasant than if "beautiful" had been flashed. Running the experiment back-to-front, Bem found that the priming effect seemed to work backwards in time as well as forwards.
Subliminal advertising comes to mind. Nothing new here.
 In another test, for instance, volunteers were told that an erotic image was going to appear on a computer screen in one of two positions, and asked to guess in advance which position that would be. The image's eventual position was selected at random, but volunteers guessed correctly 53.1 per cent of the time.
What you mean out of a choice of two theres virtually a 50/50 split in right and wrong choices. Who'd have thought it.
 That may sound unimpressive – truly random guesses would have been right 50 per cent of the time, after all. But well-established phenomena such as the ability of low-dose aspirin to prevent heart attacks are based on similarly small effects
They help prevent heart attack. As in you take them in the hope they help you (hence the small odds of them actually working - it works for some people so others try it). Nobody is claiming they definitely will prevent heart attacks. The odds are low for them because they only assist with this.
These people are using similarly low odds to claim precognition exists without any basis.

And any of this has what to do with precognition? Aside from that 50/50 test with the porn I see no reason to ascertain precognition's existence. I'd want that test reapeated many times to hold that there are >50% correct guesses occurring. But even then I'd still wouldn't hold out much for it. Why not do it with 5 / 10 / 15 pics? If precognition actually exists it would still show up, and wouldn't be so close to an even draw (as you'd expect without precognition).
 Mentor Blog Entries: 4 I loved the aspirin bit, that was so off the wall and of no significance to this, I'm still scratching my head on that one.

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 Quote by FlexGunship I believe the goal was to illustrate that "although 53% might sound very close to 50%... aspirin is recommended because instead of helping 50% of people, it helps 53% of people." Therefore, we are to conclude that 53% is, indeed, a statistically significant number.
Edit by Evo: AAAARRGH, flex, I accidently edited out your post. I need to stop answering the phone when I'm responding.
 Mentor Blog Entries: 4 Still meaningless when the discussion is about guessing something. If I only performed my job correctly 53% of the time, I'd be fired. If a doctor killed 47% of his patients it would be unacceptable. Know what I mean?

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 Quote by FlexGunship Edit by Evo: AAAARRGH, flex, I accidently edited out your post. I need to stop answering the phone when I'm responding.
Wait... where IS my response? My well-reasoned, carefully thought out post seems to have gone decidedly AWOL.

You mean... you... edited it.. out.

Everyone keeps deleting my posts...

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 Quote by FlexGunship Wait... where IS my response? My well-reasoned, carefully thought out post seems to have gone decidedly AWOL. You mean... you... edited it.. out. Everyone keeps deleting my posts...
I didn't just delete it, I sent it into oblivion.

And it was a truly great post.

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 Quote by Evo I didn't just delete it, I sent it into oblivion.
That's nothing. I once got an entire thread deleted.

(Edited for increased cleverness)

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 Quote by jarednjames Spooky my a**. All they've said there is that a student has shown they remembered a word and then when asked to type some words later that is one of the ones the typed. Would you believe it.
Heh, good point. "Researchers have demonstrated that they can get students to type words that they have previously remembered when asked."

 Quote by jarednjames Subliminal advertising comes to mind. Nothing new here.
Well, they're saying it works in reverse. Seeing the word "ugly" before seeing a kitten delays your response on the quality of the kitten. They are claiming that after you delay your response on the quality of a kitten, then will show the word "ugly."

Show word -> show cat -> delay -> judgement
Show cat -> judgement

Bem's version:
Show cat -> delay -> judgement -> show word
Show cat -> judgement

They are talking about moving the word but not moving the delay.

Again, I would like to see the response of the testee input into a supercomputer and if they show a delay, then have a supercomputer NOT display the word "ugly" afterwards. Then what do they attribute the delay to? Or does the universe simply fall apart?

 Quote by Evo: Destroyer of Posts! I loved the aspirin bit, that was so off the wall and of no significance to this, I'm still scratching my head on that one.
I believe the goal was to illustrate that "although 53% might sound very close to 50%... aspirin is recommended because instead of helping 50% of people, it helps 53% of people." Therefore, we are to conclude that 53% is, indeed, a statistically significant number.

I've found out the "Catch 22" here. Since scientific studies seek to establish causal relationships (i.e. this causes that), Bem will claim that such a metric is invalid since the very thing they are demonstrating is non-causal.

EDIT: Do you believe in miracles, Evo?
 Blog Entries: 8 Recognitions: Gold Member A test for precognition should be simple, shouldn't it? I propose the following: The test subject must accurately* predict a future event. The event must be something that is otherwise considered un-predictable (or of such low odds any other method wouldn't be able to determine its occurrence accurately). *Accuracy is defined here in relation to the complexity of the prediction. See following examples. Example 1 Task - A person predicts the outcome of a number of rolls of a fair dice. Accuracy Required - Due to the nature of the task, the person must predict the exact result. Additional Requirements - The dice must be rolled a number of times to ensure the probability of simply guessing the outcome correctly each time is made as low as possible. Recomendation is 20 rolls as a start. Example 2 Task - A person predicts a seemingly random event, in this case we'll use a car crash. Accuracy Required - The event must be described in enough detail so that a random person could match the description to the crash should it occur, without any details being left vague or open to interpretation. "A car will crash on the M4 tomorrow" is not a valid predicition. "A blue Ford will crash into a red Hyundai near junction 10 on the M4 tomorrow" is acceptable, but more detail would be preferred. Additional Requirements - As above, the event must clearly match the description given in order to be considered an accurate prediction of said event. As you can see, all you need to do is describe a future event in enough detail for us to clearly identify it when it occurs. Simple.

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 Quote by jarednjames A test for precognition should be simple, shouldn't it? I propose the following: [...] Simple.
I think the idea is that this is an unconscious response. And that it is uncontrollable by the individual. Specifically, they are saying that psychological tests are functional even if causality is reversed.

Examples of standard tests:
1. Show a scary picture -> heart rate increases
2. Show a boring picture -> heart rate steady

Examples of precognition tests:
1. Heart rate increases -> show a scary picture
2. Heart rate steady -> show a boring picture

The important fact is that whether a scary picture or a boring picture is being shown is predetermined and NOT based on the heart rate. It's quite a claim!

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Quote by jarednjames
 In one experiment, students were shown a list of words and then asked to recall words from it, after which they were told to type words that were randomly selected from the same list. Spookily, the students were better at recalling words that they would later type.
Spooky my a**. All they've said there is that a student has shown they remembered a word and then when asked to type some words later that is one of the ones the typed. Would you believe it.
I think you might be misinterpreting the experiment, maybe. The article is ambiguous, and not well written on this point, but here is how the experiment was apparently done (I'll try to summarize it):

The entire process for each participant was done in private on a computer. There were a total of 100 precipitants.
1. A list of 48 common words are given to the participant to remember. The word list and word order are identical for all test subjects. I'll call this word list the "super-set."
2. The test subject is then asked to recall as many words as they could from the superset. I'll call this list of a test subject's recalled words the "recalled-set."
3. The computer randomly generates a subset of 24 words from the super-set. This list of words is called the "practice-word-set" (the draft version of the paper calls them the 24 "practice words"). Participants then had to perform some exercises on each word, such as clicking on each word with the mouse, categorizing each word (all words form the superset are are either foods, animals, occupations, or clothes), and typing each practice word.
4. I'll call the remaining 24 words from the super-set that are not in the practice-word-set the "control-word-set" (the paper calls them "control words").
5. A measure is calculated called a "weighted differential recall (DR) score," ranging from -100% to 100%, which correlates the recalled-set to the practice-word-set and control-word-set. A positive DR% means the words from the recalled-set had a higher percentage of "practice words" than "control words." A negative DR% means the words from the recalled-set had a higher percentage of "control words" than "practice words." A 0 DR% means that the participant chose an equal number of words from both sets.
The DR score was calculated as follows,
P: number of words in both the recalled-set and practice-word set.
C: number of words in both the recalled-set and control-word set.
DR% = [(P – C) × (P + C)]/576

{Edit: Here's an example: 10 practice words recalled, 8 control words recalled. DR% = 100% x [(10-8)(10+8)]/576 = 6.25%}
There was also a 25 person control group. In this group, the procedure was the same except the participants did not do any practice exercises, and were not shown the randomly generated practice-word-set. However it was still used to calculate a DR% score for comparison.

Results:
Mean DR% score:
Main group:2.27%
Control group: 0.26%

A variation of the experiment was performed which had a slight change of how the superset of words were originally given to the participants. In this version of the experiment, the sample size was much smaller; only 50 participants. There was also a 25 participant control session.

Mean DR% score:
Main group:4.21%
Control group: Not given in the paper, but only mentioned as, "DR% scores from the control sessions did not differ significantly from zero."

For details, here's a link to where I gathered this:
http://dbem.ws/FeelingFuture.pdf

I'd like to see the experiment reproduced with a larger sample size. For now I am not impressed. And why does the paper not give the control group's mean DR% in the second experiment ?!? Perhaps because all DR% scores in the whole experiment do not statistically differ significantly from 0? I'm not impressed.

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 Quote by Evo Flex and Jared, you guys are discussing the wrong paper. You're discussing the crackpot Radin paper that Ivan posted. He was thinking of an older unrelated paper.
http://www.apa.org/pubs/journals/psp/index.aspx 0022-3514/10/$12.00 DOI: 10.1037/a0021524 This article may not exactly replicate the final version published in the APA journal. It is not the copy of record. Feeling the Future: Experimental Evidence for Anomalous Retroactive Influences on Cognition and Affect Daryl J. Bem Cornell University  Recognitions: Gold Member Science Advisor Staff Emeritus Actually, I didn't even link it, I just quoted from the paper linked in the op. Blog Entries: 8 Recognitions: Gold Member  Quote by collinsmark I think you might be misinterpreting the experiment No misinterpretation about it, that is what the article said. 53% means you are only 3% over the expected 50/50 odds of guesswork. Without a much larger test group that 3% doesn't mean anything. It could simply be a statistical anomaly. Any of you seen the Derren Brown episode where he flips a coin ten times in a row and it comes out a head each time? The test group is too small and this 3% doesn't show anything. If I sat in a room and flipped a coin 100 times, calling heads each time, there is a an equal chance that heads will come up as tails and so although you'd expect an even spread of heads vs tails, however there is a chance that you get more heads than tails and as such would show me as being correct >50% of the time. But there's nothing precognitive about that. Also, as per the Derren Brown experiment, I flip a coin ten times and could call heads ten times in a row and each coin toss come out heads. Again, nothing precognitive there. Despite what it looks like. As a note, DB spent 8 hours stood in front of a camera flipping the coin until it came out heads ten times in a row (they showed this at the end). He used it to explain something in a show (he made out it was extremely likely to happen to help what he was trying to get the audience to do), but the purpose of the explanation (showing the 8 hours worth of attempts) at the end was him trying to demonstrate that it is possible for heads to come out ten times in a row, how unlikely it was - but not impossible.  Recognitions: Gold Member Homework Help Considering the experiment involving the word memorization followed by the "practice" typing of a random subset of words, Now I am kinda' impressed. (But not jumping out of my seat or anything). I just created a C# program to simulate Daryl J. Bem's experiment in order to analyze the statistics. Basically, the program simulates the experiment, except without any human interaction so we can rule out any human influences. This way one can compare the paper's reported DR% against simulated DR% values. When simulating 100 participants in a given experiment, and repeating the experiment 5000 times, the mean DR% was very close to 0 as expected, but the standard deviation of the mean DR% was only 1.097%. The paper's reported DR% (for the first trial of 100 participants) was 2.27%. That's over two standard deviations better than expected. That could be significant. For the second trial with 50 participants, repeating the experiment 5000 times, the simulated mean was (of course) almost 0, and the standard deviation of the mean DR% was 1.54%. The actual experiment apparently had a DR% of 4.21%. That's about 2.7 standard deviations away from what is expected. So, the numbers in this experiment might be somewhat statistically significant. But I still would be curious to see how it turns out with a larger sample set. I've attached the code below. Please forgive my poor coding, I wasn't putting a whole lot of time into this. Code: //Written by Collins Mark. using System; using System.Collections.Generic; using System.Linq; using System.Text; namespace Precognition_tester { class Program { static void Main(string[] args) { int NumLoops = 5000; // <== number of experiments int SampleSize = 100; // <== number of participants in each experiment. double memoryMean = 18.4; // <== averge number of words recalled. double memoryStDev = 5; // <== standard deviation of number of words // recalled (I had to guess at this one) int ItemsPerCat = 12; int i; Random uniRand = new Random(); // Load the category lists. List foodList = new List(); foodList.Add("HotDogs"); foodList.Add("Hamburgers"); foodList.Add("Waffles"); foodList.Add("IceCream"); foodList.Add("Coffee"); foodList.Add("Pizza"); foodList.Add("Guinness"); foodList.Add("SausageEggAndCheeseBiscuit"); foodList.Add("Toast"); foodList.Add("Salad"); foodList.Add("Taco"); foodList.Add("Steak"); List animalList = new List(); animalList.Add("Cat"); animalList.Add("Dog"); animalList.Add("Snake"); animalList.Add("Whale"); animalList.Add("Bee"); animalList.Add("Spider"); animalList.Add("Elephant"); animalList.Add("Mongoose"); animalList.Add("Wambat"); animalList.Add("Bonobo"); animalList.Add("Hamster"); animalList.Add("Human"); List occupationsList = new List(); occupationsList.Add("Engineer"); occupationsList.Add("Plumber"); occupationsList.Add("TalkShowHost"); occupationsList.Add("Doctor"); occupationsList.Add("Janitor"); occupationsList.Add("Prostitute"); occupationsList.Add("Cook"); occupationsList.Add("Theif"); occupationsList.Add("Pilot"); occupationsList.Add("Maid"); occupationsList.Add("Nanny"); occupationsList.Add("Bartender"); List clothesList = new List(); clothesList.Add("Shirt"); clothesList.Add("Shoes"); clothesList.Add("Jacket"); clothesList.Add("Undershorts"); clothesList.Add("Socks"); clothesList.Add("Jeans"); clothesList.Add("Wristwatch"); clothesList.Add("Cap"); clothesList.Add("Sunglasses"); clothesList.Add("Overalls"); clothesList.Add("LegWarmers"); clothesList.Add("Bra"); // Add elements to superset without clustering List superset = new List(); for (i = 0; i < ItemsPerCat; i++) { superset.Add(foodList[i]); superset.Add(animalList[i]); superset.Add(occupationsList[i]); superset.Add(clothesList[i]); } mainLoop( NumLoops, SampleSize, ItemsPerCat, memoryMean, memoryStDev, superset, foodList, animalList, occupationsList, clothesList, uniRand); } // This is the big, main loop. static void mainLoop( int NumLoops, int SampleSize, int ItemsPerCat, double memoryMean, double memoryStDev, List superset, List foodList, List animalList, List occupationsList, List clothesList, Random uniRand) { // Report something to the screen, Console.WriteLine("Simulating {0} experiments of {1} participants each", NumLoops, SampleSize); Console.WriteLine("...Calculating..."); // Create list of meanDR of separate experiments. List meanDRlist = new List(); // Loop through main big loop for (int mainCntr = 0; mainCntr < NumLoops; mainCntr++) { // create Array of participant's DR's for a given experiment. List DRarray = new List(); //Loop through each participant in one experiment. for (int participant = 0; participant < SampleSize; participant++) { // Reset parameters. int P = 0; // number of practice words recalled. int C = 0; // number of control words recalled. double DR = 0; // weighted differential recall (DR) score. // Create recalled set. List recalledSet = new List(); createRecalledSet( recalledSet, superset, memoryMean, memoryStDev, uniRand); // Create random practice set. List practiceSet = new List(); createPracticeSet( practiceSet, foodList, animalList, occupationsList, clothesList, ItemsPerCat, uniRand); // Compare recalled count to practice set. foreach (string strTemp in recalledSet) { if (practiceSet.Contains(strTemp)) P++; else C++; } // Compute weighted differential recall (DR) score DR = 100.0 * (P - C) * (P + C) / 576.0; // Record DR in list. DRarray.Add(DR); // Report output. //Console.WriteLine("DR%: {0}", DR); } // record mean DR. double meanDR = DRarray.Average(); meanDRlist.Add(meanDR); // Report Average DR. //Console.WriteLine("Experiment {0}, Sample size: {1}, mean DR: {2}", mainCntr, SampleSize, meanDR); } // Finished looping. // Calculate mean of meanDR double finalMean = meanDRlist.Average(); // Calculate standard deviation of meanDR double finalStDev = 0; foreach (double dTemp in meanDRlist) { finalStDev += (dTemp - finalMean) * (dTemp - finalMean); } finalStDev = finalStDev / NumLoops; finalStDev = Math.Sqrt(finalStDev); // Report final results. Console.WriteLine(" "); Console.WriteLine("Participants per experiment: {0}", SampleSize); Console.WriteLine("Number of separate experiments: {0}", NumLoops); Console.WriteLine("mean of the mean DR% from all experiments: {0}", finalMean); Console.WriteLine("Standard deviation of the mean DR%: {0}", finalStDev); Console.ReadLine(); } static double Gaussrand(double unirand1, double unirand2) { return (Math.Sqrt(-2 * Math.Log(unirand1)) * Math.Cos(2 * Math.PI * unirand2)); } static void createRecalledSet(List recalledSet, List superSet, double mean, double stdev, Random unirand) { // Determine how many words were recalled. (random) double unirand1 = unirand.NextDouble(); double unirand2 = unirand.NextDouble(); while (unirand1 == 0.0) unirand1 = unirand.NextDouble(); while (unirand2 == 0.0) unirand2 = unirand.NextDouble(); double gaussrand = Gaussrand(unirand1, unirand2); gaussrand *= stdev; gaussrand += mean; int recalledCount = (int)gaussrand; if (recalledCount > superSet.Count) recalledCount = superSet.Count; // Create temporary superset and copy elements over. List tempSuperSet = new List(); foreach (string strTemp in superSet) { tempSuperSet.Add(strTemp); } // Randomize temporary superset. shuffleList(tempSuperSet, unirand); // Copy over first recalledCount items to recalledSet. for (int i = 0; i < recalledCount; i++) { recalledSet.Add(tempSuperSet[i]); } } static void createPracticeSet( List practiceList, List foodList, List animalList, List occupationsList, List clothesList, int itemsPerCat, Random uniRand) { List tempFoodList = new List(); List tempAnimalList = new List(); List tempOccupationsList = new List(); List tempClothesList = new List(); // load temporary lists. foreach (string strTemp in foodList) tempFoodList.Add(strTemp); foreach (string strTemp in animalList) tempAnimalList.Add(strTemp); foreach (string strTemp in occupationsList) tempOccupationsList.Add(strTemp); foreach (string strTemp in clothesList) tempClothesList.Add(strTemp); // Shuffle temporary lists shuffleList(tempFoodList, uniRand); shuffleList(tempAnimalList, uniRand); shuffleList(tempOccupationsList, uniRand); shuffleList(tempClothesList, uniRand); // Load practice list for (int i = 0; i < itemsPerCat / 2; i++) { practiceList.Add(tempFoodList[i]); practiceList.Add(tempAnimalList[i]); practiceList.Add(tempOccupationsList[i]); practiceList.Add(tempClothesList[i]); } // Shuffle practice list shuffleList(practiceList, uniRand); } // method to shuffle lists. static void shuffleList(List list, Random unirand) { List shuffledList = new List(); while (list.Count() > 0) { int indexTemp = unirand.Next(list.Count()); shuffledList.Add(list[indexTemp]); list.RemoveAt(indexTemp); } foreach (string strTemp in shuffledList) list.Add(strTemp); } } } Mentor Blog Entries: 4  Quote by Ivan Seeking What are you talking about? This is what I linked. © 2010 American Psychological Association http://www.apa.org/pubs/journals/psp/index.aspx 0022-3514/10/$12.00 DOI: 10.1037/a0021524 This article may not exactly replicate the final version published in the APA journal. It is not the copy of record. Feeling the Future: Experimental Evidence for Anomalous Retroactive Influences on Cognition and Affect Daryl J. Bem Cornell University