It is not difficult to find a relationship where there is none. Expecting a close correlation, we easily link disparate events together, attributing an illusory relationship to them. William Ward and Herbert Jenkins introduced the subjects to the results of an experiment that allegedly took place over 50 days, the essence of which was to treat clouds with special reagents that caused rain (Ward & Jenkins, 1965). They told the subjects on which days the clouds were processed and on which days it rained. This information was nothing more than a random mix of facts: sometimes the processing and rain coincided, sometimes not. Nevertheless, the subjects, in full accordance with their ideas about the effects of reagents on clouds, were convinced that they had observed a connection between treatment and rain. The fact that random events are easily perceived by us as confirmation of our judgments has been proved by other researchers (Crocker, 1981; Jennings et al., 1982; Trolier & Hamilton, 1986). If we are convinced of the existence of a correlation, we are more likely to notice and remember relevant examples. If we believe that premonitions and subsequent events are related, we notice and remember the connection between the premonition and the event that will happen later. We rarely notice or remember all the cases of mismatch between premonitions and events. If, after we think about a friend, we hear his call, we will pay attention to this coincidence and remember it. But we don’t notice or remember those episodes when we thought about him, but he didn’t call us, or when a person called whom we hadn’t thought about before. People see not only the correlations they expect, but also the ones they want to see. In one of her experiments, Mariette Berndsen and her colleagues showed its participants, students at the University of Amsterdam, the results of a survey allegedly conducted among other students at the same and another university in the Netherlands in order to find out their attitude to the transition to teaching in English (Berndsen et al., 1996). The experimenters told the subjects that the university where this idea would receive the most support would switch to teaching in English. The presented results of the “surveys” from both universities were identical. The subjects who liked this idea found a correlation in the “polls” that was not there; those who were opposed to it took the results of the “polls” as proof that students at their university objected more actively than students from another university. A person’s desire to find a connection even between random events leads to the fact that he begins to look for an explanation for unusual incidents or incomprehensible changes in mood. Whatever reason we explain the events, we make them “seemingly” more predictable and controllable and organize our world. We can only repeat that this trend, like many others, is adaptive in most cases, but sometimes it misleads us.

Our inherent tendency to perceive random events as interconnected is a breeding ground for the illusion of control, the idea that we can influence random events.She is the one who guides gambling enthusiasts, and the rest when they do all sorts of incredible things. Gambling. The illusion of control was demonstrated by Ellen Langer in gambling experiments (Langer, 1977). When the people who drew the “lucky” lottery ticket were asked to sell it, they named a price four times higher than that of the people who received it from others. When their roulette partners were inexperienced and nervous people, they made more solid bets than when they played with confident and restrained opponents. In the course of these and many other experiments (there were more than 50 in total), it was shown that people behave as if they can predict or control random events (Presson & Benassi, 1996; Thompson et al., 1998). Observations of the actions of gambling enthusiasts in real life confirmed these experimental data. Dice players can roll them delicately, believing that few points will “fall out”, and resolutely so that many will fall out (Henslin, 1967). The gambling industry thrives on the illusions of the players. Gambling enthusiasts attribute their winnings to their own skill and foresight, and their losses to “blunders” or (if we are talking about sports games) various “accidents”, for example, that “the ball ricocheted absurdly” or that “the referee blew the whistle at the wrong time” (Gilovich & Douglas, 1986). Observing that how passionately people want to control what is happening, even when it comes to choosing a lottery ticket, Ellen Langer writes: “I thought about those people who are practically deprived of the ability to control their lives. Studying hospital patients and residents of nursing homes, I came to the conclusion that giving them the right to at least partially control their lives improves their physical and moral condition. All this allowed me to understand that perceived control is extremely important for successful functioning” (Langer, 1999). Return to the mean. [A more accurate translation would be “regression to the norm” (regressiontowardtheaverage); we use “return to the mean” in order not to break the already established tradition. — Notable scientific ed. Another path potentially capable of leading to illusory thinking is described by Tversky and Kahneman: we fail to recognize a statistical phenomenon called return to the mean (Tversky & Kaheman, 1974). Since the fluctuation in exam grades is partly an accident, most students who get exceptionally high marks on the current exam will not pass the next one so successfully. Since the first estimate is their “ceiling,” the next one will mark a return to the usual average rather than raise the bar even higher. (This is why a student who works consistently but is never considered an excellent student often finishes the course among the best.) As for the student who got the lowest score on the first exam, it is very likely that he, on the contrary, will pass the next exam better. If those who get the lowest scores start studying with a tutor after the exam, and then pass the exam more successfully, the tutors will most likely decide that the lessons with them were beneficial, even if in fact they were ineffective. {Return to the average. If we are at an exceptionally low level, as a rule, any attempts to correct the situation will seem successful when we return to our normal state.} And that’s right: when everything starts to fall out of hand, we take any steps to fix the situation: we turn to a therapist, go on a new diet and start doing new exercises, read popular literature about self-help. The situation is likely to improve rather than worsen. Sometimes it “dawns on us” that extreme situations, both bad and good, must come to an end at some point. Life has taught us that when everything goes too well, some kind of trouble is bound to happen, and when life hits us hard, there is always the opportunity to keep hope for a better future. However, we often do not recognize this regression effect. We are puzzling over why the baseball star of last season is achieving quite ordinary results this year. Was he being conceited? Or maybe he’s become overconfident? We forget that exceptional achievements tend to regress, i.e., to return to a normal level. By simulating the effects of rewards and punishments, Paul Schaffner proved that the illusion of control can also permeate human relationships (Schaffner, 1985). He conducted an experiment with Bowden College students who had to teach a fictional fourth-grader named Harold to come to school at 8:30 every day. For three weeks, the computer regularly recorded Harold’s arrival time, and it turned out that he always came to school between 8.20 and 8.40. Having found out this, the participants in the experiment had to decide how to react to Harold’s behavior, and this reaction could be anything from excessive praise to severe punishment. As you may have guessed, Harold was praised for arriving early, and scolded for being late. Since the computer was programmed by Schaffner to randomly alternate Harold’s early arrivals and his lateness, the punishments contributed to the formation of a tendency to “correct” him (arrival time shifted to 8.30). For example, if Harold came to school at 8:39 a.m., he knew for sure that he would be reprimanded, and the probability that he would arrive earlier than 8:39 a.m. the next day was very high. Consequently, even though their punishments had no effect on Harold, after completing the experiment, most of his participants found them effective. This experiment confirms Tversky and Kahneman’s audacious conclusion: nature works in such a way that we often feel punished for rewarding others and rewarded for punishing them. In fact, as every psychology student knows, positive reinforcement for correct behavior is usually more effective and has very few side effects. Source: Myers D. “Social Psychology” Photo: u-mama.ru