The And Of A Bernoulli Random

On the other hand, most humans understand the fact that everything happens for a reason, every action has a reaction and the world runs on cause and effect. The leaf on the tree falls because the wind blow.This “philosophical position” [1] is called Determinism.

Pascal’s Wager has been argued to be impractical because our beliefs are often not in our control. This argument is

When a state of probability remains undetermined, we often feel compelled to define it. We desire certainty, so we obtain it through whichever way we see fit, even when it is unattainable or harmful to do so. When we imagine

Randomness error: the tendency of individuals to believe that they can predict the outcome of random events.

When humans make a decision, it often turns out to be “predictably irrational” (Ariely, 2009). They always deviate systematically from expected decision rather show an inclination towards a certain way of thinking. This consistency of behavioral or decision bias can be very helpful to identify consequences or outcomes in a different

In this experiment, we will investigate whether previous participation in a confirmation bias experiment plus full knowledge of confirmation bias and the Wason 2-4-6 paradigm will lead to a higher initial success rate with future testing. A confirmation bias usually occurs when participants are trying to confirm their beliefs during an experiment. During these experiments, participants results varied between confirmatory and disconfirmatory. The Tukey HSD that was performed for the experiments showed some significance in certain areas. For instance, there was a statistical significance for the total number of guesses between rule one and rule three. More simply, in the first experiment the results showed participants used confirmatory method more for rule one than rule three. For the second experiment participants had more knowledge about the experiment, so their use of the confirmatory method decreased. However, in the second experiment participants used disconfirmatory more for rule three than they did in rule one. Furthermore, all the experiments were similar, because participants had to guess a rule based off a three-number sequence.

problem. The Monty Hall Math problem led Christopher to believe that people rely on their intuitions

One of the biases that have been proposed by Kahneman and Tversky, and researched a great deal is the Availability bias. Availability bias is the concept of giving first choice to events and information because they are often more recent or giving preference to events, observed personally. Senior managers and decision makers are often victims of availability bias. Availability bias occurs when decision makers estimate the probability of outcome based on how prevalent the outcome appears in their lives (Pompian, 2011)

Nassim Nicholas Taleb, the author of ‘Fooled by the Randomness’ discusses whether modern humans are often unware of the existence of randomness. Taleb argues that humans tend to explain random outcomes as non-random, a provocative opinion which has really inspired me to take further interest in Statistics.

Freewill has been thoroughly discussed by ancient philosophers and modern scientist alike yet no conclusion has ever been reached. With the issue that whether freewill is consistent or inconsistent with the idea that everything happens out of mechanistically that is deemed appropriate by the universe. There are three common camps of thoughts on the matter of free will. Determinism and Libertarianism and Compatibilism. This essay argues the fact that freewill is indeed not an illusion and attempts to redress the balance between these camps of thoughts by offering an overview of strategy via that of a compatabilism point of view.

Prior to the start of the game, after all individuals were randomly seated, we gave a short demographic survey. Then participants took the UPPS-P Impulsive Behavior Scale (Whiteside & Lynam, 2001), which is used to measure personality traits, as described in Section 3.2, followed by the Balloon Analogue Risk Task (BART), which is used to measure risk taking (Lejuez et al., 2002).

Researchers of this particular study argue the gambler’s fallacy is due to at least two particular errors in reasoning: (1) the perception of discrete events as being interrelated or part of a pattern and (2) the belief events will equalize in the short term (for example, expecting heads to appear 50% of the time in a trial of ten coin flips). As previous studies and examinations of the fallacy focused primarily on the second error in thinking, this study focused primarily on the former.

On the other hand, most of our knowledge leads us in the direction of believing the universe’s functions are deterministic. That is, our knowledge tells us that choice is not necessary to our description of the universe. Events occur as a result of the events which preceeded them. For example, if we strike the cue-ball properly, the 8-ball will be knocked into the billiard table pocket which

The Gambler's fallacy, also known as the Monte Carlo fallacy (because its most famous example happened in a Monte Carlo Casino in 1913)[1] . Also referred to as the fallacy of the maturity of chances, which is the belief that if deviations from expected behaviour are observed in repeated independent trials of some random process, future deviations in the opposite direction are then more likely. For example, if a fair coin is tossed repeatedly and tails comes up a larger number of times than is expected, a gambler may incorrectly believe that this means that heads is more likely in future tosses.[2] . Such an expectation could be mistakenly referred to as being due, and it probably arises from

My title of the exploration is “Analyzing of the Gambler’s Fallacy”. An analytical approach to the Gambler’s Fallacy, so that I can know how accurate is the probability of the Gambler’s Fallacy. According to the Investopedia, “When an individual erroneously believes that the onset of a certain random event is less likely to happen following an event or a series of events. This line of thinking is incorrect because past events do not change the probability that certain events will occur in the future.” Gambler’s Fallacy is about our incorrect thinking of predicting what will happen next by the events happened before or the previous probability. For example, I did a coin toss for 10 times and I got 8 heads and 2 tails. According to the Gambler’s Fallacy, it is less likely to have head because it is frequently happened in the previous 10 trials. Although, the probability of having head or tail does not matter with the previous probabilities of the 10 coin toss.