Monday, 27 December 2010
Final Coursework
The last couple weeks went really fast! I will miss this module because during the years all I have gained was mainly theoretical side of the things, however, this module gave me both theory and practical. The weekly exercise or group work motivates you to learn more about subjects and be able to discuss it, which really built up my confidence in talking in front of the class. I found most if not all the topics very interesting this could be because I made an effort to go extra mile in finding information every week, which I don't do that often but the way David teach this module is impossible to not do so. Last weeks work is one of my favourite topics of the module "Terrorism" because I always wanted to understand how people deal or felt about terrorist attacks, specially after 9/11. My paper was based on Lopez report on Train attacks in Madrid, which killed around 200 people. Lopez wanted to establish whether the Spanish people behaved in the same way as Americans after the terrorist attacks. As we all know the 9/11 had huge impact on Americans and the rest of world. After 9/11 many Americans avoided air travel and they used more cars on the road instead, which according to some is more risky than traveling by plane. The results of more cars on the road caused many accidents and fatal death in America. Lopez suggested that the Spanish, however, still travelled by train after the attacks and had less accidents or fatal deaths. This shows that terrorist attacks did not change Spanish day to day live. There are many reasons behind this such as, 9/11 attacks caused more death than Madrid attacks, Americans use more cars than Spanish or maybe American people may have used unfamiliar roads after the attacks so on. Lopez mentioned one important point, which could really explain the causes of Spanish people indifference's towards terrorist attacks. He said maybe Spanish people were familiar with terrorist attacks for many years so this could just be other one for them. I do understand the reaction of American people because it doesn't really matter the scales of terrorist attacks, they all have big impact whether it is physical or psychological. Individuals live in fear as the attacks could be anytime and anywhere. After what happened in London I do get very conscious in travelling by train or even buses so I am forced to drive my car around, however, this doesn't mean that I'm safe, all I need to do is learn how to live with this fear and find best strategy for coping with it.
Friday, 19 November 2010
Trouble with my Wiki Posts
I Had difficult and frustrating time with my mid semester course work for all week. I requested help from tutor and colleagues but I did not get any reply what so ever. The only thing that I could think of is to post it on my Blog but it is really annoying to have the work done and not been able to share it with others for comments or simply be able to comment on others as well. I felt really lonely for a while! However, I managed to sort things out on Friday with David.
Image from google gallery
Last weeks lecture on Coorporation and Coordination was very interesting and a bit difficult to grasp at first but if you manage to understand it then you get to see the interesting side of it. Nash thoery was really interesting but I just think that at certain time we are just too busy to perform such mathematical calculations in short period of time.
Image from google gallery
Last weeks lecture on Coorporation and Coordination was very interesting and a bit difficult to grasp at first but if you manage to understand it then you get to see the interesting side of it. Nash thoery was really interesting but I just think that at certain time we are just too busy to perform such mathematical calculations in short period of time.
Thursday, 18 November 2010
Expected utility theory
Chapter 7
2 - In what ways have people been observed to violate expected utility theory?
Expected utility theory suggests that rational decision makers should weight the utilities of outcomes by their probability of occurrence. According to Baron (2000), expected utility theory as descriptive model of decision making under risk and it deals with those decisions that can be seem as gamble and gamble as one knows does not indicate any knowledge of prospect, so therefore, individual’s base their decision mainly on probabilities. Expected utility theory has always been accepted as a normative model rational choice and largely applied as a descriptive model of economic behaviour and it assumes that all reasonable individual would wish to obey the axioms of the theory, and that most people actually do majority of time.
According to Baron (2000), the use of expected value as a way of deciding about the money gamble seems fairly reasonable if individuals who want to choose between two gambles and it would make more sense to take the one with higher expected value, so that their average winning will get closer to the expected value itself. Utility judgment are useful in making important decisions, however, as the expected utility theory is a normative model, this means if individuals try to calculate expected utility for every decisions they make it will mean that they would have to spend a lot of time making calculations. However, instead of doing this we should simply familiarize ourselves with more prescriptive rules of different sorts such as, moral and personal behaviour rules. Expected utility theory seems to be a useful and adequate model of risk aversion for many purposes, and it is especially attractive in lieu of an equally obedient alternative model. Rabin (2000) suggests that extremely concave expected utility may even be useful as a parsimonious tool for modelling aversion to modest scale risk.
However, many researchers criticised expected utility theory due to the fact that they believe that this is descriptive model of decision making under risk and so alternative model was created known as prospect theory. According to this theory choice among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular an individual underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty, and this contributes to risk aversion in choices involving sure gains and to risk seeking in choices of sure loses. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gamble. Hardman (2009), suggests that prospect theory can be considered as a psychological variant of subjective to expected utility theory. Many decision makers are involved in process of editing stage whereby they first structure the decision problem in such a way as to simplify sequent evaluations and choice. This is important because it allows the decision makers to determine the potential outcomes as gains and loses relative to some reference point often known as status quo and at the evaluation stage; both a value function and weighting are applied to prospect.
In conclusion, utility theory as normative model suggests that the way of achieving good decisions comes from goals. Isenberg (1989) Researches in the area of individual decision behaviour and strategic decisions, however, has indicated that individual do not always behave according to the assumptions of utility theory. That is, they do not seek to know all possible outcomes, always assign accurate probabilities to the outcomes they recognise or consistently select the best payoff from considered alternatives.
References:
Baron, J. (2000). Thinking and Deciding (3r edition). Cambridge University Press,
Hardman, D. (2009). Judgment and Decision Making: Psychological Perspectives. BPS Blackwell
2 - In what ways have people been observed to violate expected utility theory?
Expected utility theory suggests that rational decision makers should weight the utilities of outcomes by their probability of occurrence. According to Baron (2000), expected utility theory as descriptive model of decision making under risk and it deals with those decisions that can be seem as gamble and gamble as one knows does not indicate any knowledge of prospect, so therefore, individual’s base their decision mainly on probabilities. Expected utility theory has always been accepted as a normative model rational choice and largely applied as a descriptive model of economic behaviour and it assumes that all reasonable individual would wish to obey the axioms of the theory, and that most people actually do majority of time.
According to Baron (2000), the use of expected value as a way of deciding about the money gamble seems fairly reasonable if individuals who want to choose between two gambles and it would make more sense to take the one with higher expected value, so that their average winning will get closer to the expected value itself. Utility judgment are useful in making important decisions, however, as the expected utility theory is a normative model, this means if individuals try to calculate expected utility for every decisions they make it will mean that they would have to spend a lot of time making calculations. However, instead of doing this we should simply familiarize ourselves with more prescriptive rules of different sorts such as, moral and personal behaviour rules. Expected utility theory seems to be a useful and adequate model of risk aversion for many purposes, and it is especially attractive in lieu of an equally obedient alternative model. Rabin (2000) suggests that extremely concave expected utility may even be useful as a parsimonious tool for modelling aversion to modest scale risk.
However, many researchers criticised expected utility theory due to the fact that they believe that this is descriptive model of decision making under risk and so alternative model was created known as prospect theory. According to this theory choice among risky prospects exhibit several pervasive effects that are inconsistent with the basic tenets of utility theory. In particular an individual underweight outcomes that are merely probable in comparison with outcomes that are obtained with certainty, and this contributes to risk aversion in choices involving sure gains and to risk seeking in choices of sure loses. Overweighting of low probabilities may contribute to the attractiveness of both insurance and gamble. Hardman (2009), suggests that prospect theory can be considered as a psychological variant of subjective to expected utility theory. Many decision makers are involved in process of editing stage whereby they first structure the decision problem in such a way as to simplify sequent evaluations and choice. This is important because it allows the decision makers to determine the potential outcomes as gains and loses relative to some reference point often known as status quo and at the evaluation stage; both a value function and weighting are applied to prospect.
In conclusion, utility theory as normative model suggests that the way of achieving good decisions comes from goals. Isenberg (1989) Researches in the area of individual decision behaviour and strategic decisions, however, has indicated that individual do not always behave according to the assumptions of utility theory. That is, they do not seek to know all possible outcomes, always assign accurate probabilities to the outcomes they recognise or consistently select the best payoff from considered alternatives.
References:
Baron, J. (2000). Thinking and Deciding (3r edition). Cambridge University Press,
Hardman, D. (2009). Judgment and Decision Making: Psychological Perspectives. BPS Blackwell
Representativeness and Availability Heuristics
Chapter 3
4 – What do think are the advantages and disadvantages of using heuristics like representativeness and availability?
Heuristics as a term means a method that help solve problems. Representativeness heuristics was first conned by Kahneman and Tversky while they were conducting research on judgment. Heuristics are recognised for their fast conclusion to a decision and representativeness heuristic is very useful for everyday decision making. However, the use of representativeness heuristics as any heuristics can lead to errors and neglect of other cognitive tasks. According to Kahneman and Tversky representativeness heuristics can lead to biases by believe that causes and effects will resemble one and other.
Although, it effectiveness representativeness heuristics can violate of the fundamental properties of probabilities such as, extensionality. Let’s for example take the problem proposed by Kahneman and Tversky about LINDA, who according to the characteristics resemble a feminist. The participants were asked to evaluate the probabilities of LINDA been a bank teller, feminist or probability of her being both bank teller and feminist. According to the probability theory the probability of her being both bank teller and feminist is must been less or equal to her being feminist or bank teller. However, the participant’s judgments were that she must have been bank teller and feminist.
Apart from the violation of extensionality, representativeness heuristics also violates base-rate and conjunction fallacy and also the use of representativeness heuristics may also lead to disjunction fallacy. Probability theory tells us that disjunction of two events is at least as likely as either of the events individually. Studies suggests that even though individuals are aware that statistical mode of reasoning is appropriate, they are often unable to correctly apply this intuition and instead they use the representativeness heuristics (Hardman, 2009)
Availability Heuristics
According to Tversky (1982), availability is an ecologically valid clue for the judgment of frequency this is because in general, frequent events are easier to recall or imagine than infrequent ones (cited in Kahneman et al 1982, p. 164). Availability heuristics suggests that we use the knowledge that is readily available rather than looking at other alternatives. When it comes to availability heuristics as studies suggested imagining a situation has better results than asked to think of specific situation. However, the overreliance on availability heuristics can lead to biases such as irretrievability of instances, the effectiveness of search set and also illusory correlation. One can argue that perceived causes of imagined events that was mentioned by Tversky (1982) might have impact on probability estimates.
Conclusion, on one hand, when individuals use representativeness heuristics what they are doing in fact is changing a judgment of probability with the similarity. This however, moves from the typical answer suggested by the theory of probability. On the other hand, availability heuristics is more dependent on memory. Availability is associated with recency effect for recalls and also with familiarity to certain things and situations. Both representativeness and availability heuristics have their usefulness, however, to reduce error we should not rely on them as they might lead to errors.
4 – What do think are the advantages and disadvantages of using heuristics like representativeness and availability?
Heuristics as a term means a method that help solve problems. Representativeness heuristics was first conned by Kahneman and Tversky while they were conducting research on judgment. Heuristics are recognised for their fast conclusion to a decision and representativeness heuristic is very useful for everyday decision making. However, the use of representativeness heuristics as any heuristics can lead to errors and neglect of other cognitive tasks. According to Kahneman and Tversky representativeness heuristics can lead to biases by believe that causes and effects will resemble one and other.
Although, it effectiveness representativeness heuristics can violate of the fundamental properties of probabilities such as, extensionality. Let’s for example take the problem proposed by Kahneman and Tversky about LINDA, who according to the characteristics resemble a feminist. The participants were asked to evaluate the probabilities of LINDA been a bank teller, feminist or probability of her being both bank teller and feminist. According to the probability theory the probability of her being both bank teller and feminist is must been less or equal to her being feminist or bank teller. However, the participant’s judgments were that she must have been bank teller and feminist.
Apart from the violation of extensionality, representativeness heuristics also violates base-rate and conjunction fallacy and also the use of representativeness heuristics may also lead to disjunction fallacy. Probability theory tells us that disjunction of two events is at least as likely as either of the events individually. Studies suggests that even though individuals are aware that statistical mode of reasoning is appropriate, they are often unable to correctly apply this intuition and instead they use the representativeness heuristics (Hardman, 2009)
Availability Heuristics
According to Tversky (1982), availability is an ecologically valid clue for the judgment of frequency this is because in general, frequent events are easier to recall or imagine than infrequent ones (cited in Kahneman et al 1982, p. 164). Availability heuristics suggests that we use the knowledge that is readily available rather than looking at other alternatives. When it comes to availability heuristics as studies suggested imagining a situation has better results than asked to think of specific situation. However, the overreliance on availability heuristics can lead to biases such as irretrievability of instances, the effectiveness of search set and also illusory correlation. One can argue that perceived causes of imagined events that was mentioned by Tversky (1982) might have impact on probability estimates.
Conclusion, on one hand, when individuals use representativeness heuristics what they are doing in fact is changing a judgment of probability with the similarity. This however, moves from the typical answer suggested by the theory of probability. On the other hand, availability heuristics is more dependent on memory. Availability is associated with recency effect for recalls and also with familiarity to certain things and situations. Both representativeness and availability heuristics have their usefulness, however, to reduce error we should not rely on them as they might lead to errors.
Tuesday, 16 November 2010
Mid Semester Work
Chapter 1
6 - Compare and contrast the fast and frugal approach to judgment with the regression analysis approach.
Reasoning is one of the important ability that both humans and animals can acquire. However, this is considered being very complex and for many years it has generated numerous studies. From the minute we wake up until the minute we go to sleep we make judgments and decisions about things, peoples and situations. Gigerenzer and colleagues (1991) suggested that humans and animals make inferences about the world under limited time and knowledge. Rationality and optimality are the guiding idea of the probabilistic approach to cognition but they are not the only reasonable guiding ideas. They suggested that there are other concepts such as simplicity and frugality, which have also inspired models of cognition. Fast and frugal models are justified by their psychological plausibility and datedness to natural environment and also are easier to understand.
Gigerenzer and colleagues (1989) also suggested that these fast and frugal violate fundamental views of classical rationality; they neither look up nor integrate all information. Even though these fast and frugal heuristics are good they are however, under constant criticism for example, Hardman (2009) suggests that these fast and frugal heuristics does not tell us what is going on in the mind of decision maker during the process of judgment.
Gigerenzer et al (1996) suggested that many studies been conducted in order to test the validity of these two views by identifying conditions under which the human mind appears more rational or irrational. However, most of the works have mainly focused in simple situations, such as Bayesian inference with binary hypotheses, one single piece of binary data, and all necessary information conveniently laid out for the participant. In many real world situations, however, there are pieces of information which are not independent. Bayes’ theorem and other rational algorithms quickly become mathematically complex and computationally intractable, at least for human minds.
A number of heuristics or short cuts are used to make fast and frugal judgments such as recognition heuristics. According to the probabilistic mental model theory inferences about the unknown states of the world are based on probability cues, such as football team, universities and so on. Gigerenzer and colleagues (1996), created a scenario whereby the participants must make a choice between two alternatives, such as on a dimension of a city. The two alternatives choice tasks occur in different contexts in which inferences need to be made with limited time and knowledge. Their study of two alternative choice tasks in situations where a person has to make an inference based only on knowledge retrieved from memory, which implies that the participants need to use their declarative knowledge to perform the task.
According to Gigerenzer el at (1996), probabilistic mental model is an inductive device that uses limited knowledge to make fast references and they perform intelligent guesses about unknown features of the world, based on uncertain indicators. To make inferences about which one of the cities has higher population (a or b), then knowledge about the reference class, for example, cities in Germany could be searched. Limited knowledge indicates that the matrix of objects by cues has missing entries i.e. objects, or cues or even cue value which might be unknown.
On the other hand we have regression analysis approach, which according to studies takes more time and are cognitively more demanding. Regression analysis usually traces the distribution of the self-governing variable (y) or some characteristic of this distribution (x). However, according to Fox there are advantages of approaching regression analysis from a general perspective. On the one hand, the appreciation for the practical problems of fitting the general models implies the specification of more limiting models such as the use of the usual linear regression model with standard errors. On the other hand, modern methods of nonparametric regression, while not quite as general as models are emerging as the practical alternatives to the more traditional linear models.
Aminta
6 - Compare and contrast the fast and frugal approach to judgment with the regression analysis approach.
Reasoning is one of the important ability that both humans and animals can acquire. However, this is considered being very complex and for many years it has generated numerous studies. From the minute we wake up until the minute we go to sleep we make judgments and decisions about things, peoples and situations. Gigerenzer and colleagues (1991) suggested that humans and animals make inferences about the world under limited time and knowledge. Rationality and optimality are the guiding idea of the probabilistic approach to cognition but they are not the only reasonable guiding ideas. They suggested that there are other concepts such as simplicity and frugality, which have also inspired models of cognition. Fast and frugal models are justified by their psychological plausibility and datedness to natural environment and also are easier to understand.
Gigerenzer and colleagues (1989) also suggested that these fast and frugal violate fundamental views of classical rationality; they neither look up nor integrate all information. Even though these fast and frugal heuristics are good they are however, under constant criticism for example, Hardman (2009) suggests that these fast and frugal heuristics does not tell us what is going on in the mind of decision maker during the process of judgment.
Gigerenzer et al (1996) suggested that many studies been conducted in order to test the validity of these two views by identifying conditions under which the human mind appears more rational or irrational. However, most of the works have mainly focused in simple situations, such as Bayesian inference with binary hypotheses, one single piece of binary data, and all necessary information conveniently laid out for the participant. In many real world situations, however, there are pieces of information which are not independent. Bayes’ theorem and other rational algorithms quickly become mathematically complex and computationally intractable, at least for human minds.
A number of heuristics or short cuts are used to make fast and frugal judgments such as recognition heuristics. According to the probabilistic mental model theory inferences about the unknown states of the world are based on probability cues, such as football team, universities and so on. Gigerenzer and colleagues (1996), created a scenario whereby the participants must make a choice between two alternatives, such as on a dimension of a city. The two alternatives choice tasks occur in different contexts in which inferences need to be made with limited time and knowledge. Their study of two alternative choice tasks in situations where a person has to make an inference based only on knowledge retrieved from memory, which implies that the participants need to use their declarative knowledge to perform the task.
According to Gigerenzer el at (1996), probabilistic mental model is an inductive device that uses limited knowledge to make fast references and they perform intelligent guesses about unknown features of the world, based on uncertain indicators. To make inferences about which one of the cities has higher population (a or b), then knowledge about the reference class, for example, cities in Germany could be searched. Limited knowledge indicates that the matrix of objects by cues has missing entries i.e. objects, or cues or even cue value which might be unknown.
On the other hand we have regression analysis approach, which according to studies takes more time and are cognitively more demanding. Regression analysis usually traces the distribution of the self-governing variable (y) or some characteristic of this distribution (x). However, according to Fox there are advantages of approaching regression analysis from a general perspective. On the one hand, the appreciation for the practical problems of fitting the general models implies the specification of more limiting models such as the use of the usual linear regression model with standard errors. On the other hand, modern methods of nonparametric regression, while not quite as general as models are emerging as the practical alternatives to the more traditional linear models.
Aminta
Monday, 24 May 2010
Week 6 Preference and Choice
Rational choice theory suggests that individual have preferences that are manifested in their behaviour. However, some researches suggest that individuals construct their preferences in process of thinking about their choice. (Slovic et al, 2006) We do make choices that are sometimes regretful if of course the wrong mode of evaluation is applied, that is the reason why we do sometimes spend enough time comparing between alternatives. Probability is taken into consideration for many decisions and the decision maker normally use expected value expected utility theory and this is in fact considered to be the most accurate choice strategy but also most effortful because it requires the use all information necessary and all alternatives.
It is believed that if the individual is aiming to achieve accuracy between alternatives they will require a considerable level of cognitive effort to do so. However, the studies with computer assimilation suggest that less effortless strategy cam also achieve accuracy but one should bear in mind that no single heuristics is accurate across all context. Kahneman and Tversky (1979) suggested that individuals evaluate outcomes as gains or losses from reference point which is normally the status quo. This generally means that individuals are loss averse and that losses appear larger than gains and most of our choices is evaluated in terms of their advantages and disadvantage relative to each other. (Hardman, 2009)
Rational choice theory suggests that individual have preferences that are manifested in their behaviour. However, some researches suggest that individuals construct their preferences in process of thinking about their choice. (Slovic et al, 2006) We do make choices that are sometimes regretful if of course the wrong mode of evaluation is applied, that is the reason why we do sometimes spend enough time comparing between alternatives. Probability is taken into consideration for many decisions and the decision maker normally use expected value expected utility theory and this is in fact considered to be the most accurate choice strategy but also most effortful because it requires the use all information necessary and all alternatives.
It is believed that if the individual is aiming to achieve accuracy between alternatives they will require a considerable level of cognitive effort to do so. However, the studies with computer assimilation suggest that less effortless strategy cam also achieve accuracy but one should bear in mind that no single heuristics is accurate across all context. Kahneman and Tversky (1979) suggested that individuals evaluate outcomes as gains or losses from reference point which is normally the status quo. This generally means that individuals are loss averse and that losses appear larger than gains and most of our choices is evaluated in terms of their advantages and disadvantage relative to each other. (Hardman, 2009)
Week 5 Decision Framing Effects
This weeks topic is about decision framing effects. When I looked at the heading I asked myself what is decision framing effect? According psychologists ‘‘framing effect’’ is observed when a decision maker’s risk tolerance, (as implied by their choices) is dependent upon how a set of options is described. Specifically, people’s choices when faced with inevitably identical decision problems framed positively (gains) versus negatively (losses) are often opposing. As suggested by the utility theory, the outcomes and associated probability is all that is needed to determine decision maker’s preference between events to the contrary to the principal of rational theory of choice. However, it is believed that many of us violate this principle. The study conducted by Kahneman and Tversky (1984) where they asked their participants to make decision about the terrible disease which is expected to kill 600 people. The participants have been given two alternatives to the problem.
A) 200 people will be saved (72%)
B) There is a 1/3 probability that 600 people will be saved and 2/3 probability that no people will be saved (28%)
As I expected many of their participants preferred the option where 200 lives will be saved. Framing effects is well known in the financial sector, for example insurance companies, and there is also evidence that positive and negative framing effects are associated with different levels of cognitive processing. Dunegan (1993), study with international company engaged in developing high technology engineering systems suggested that the positive frames stated that of the project undertaken by the team, 30 of the last 50 have been successful and the negative frame stated that of the projects undertaken by this team, 20 of the last 50 have been unsuccessful. The negative framing group allocated less money on the project and they also were more concerned in reducing the costs. (Hardman, 2009)
The question is whether or not framing is a reliable phenomenon. a meta-analysis conducted by Kuhberger (1997) suggests that framing is reliable phenomenon, however, outcome salience manipulation, which constitute a considerable amount of work.
This weeks topic is about decision framing effects. When I looked at the heading I asked myself what is decision framing effect? According psychologists ‘‘framing effect’’ is observed when a decision maker’s risk tolerance, (as implied by their choices) is dependent upon how a set of options is described. Specifically, people’s choices when faced with inevitably identical decision problems framed positively (gains) versus negatively (losses) are often opposing. As suggested by the utility theory, the outcomes and associated probability is all that is needed to determine decision maker’s preference between events to the contrary to the principal of rational theory of choice. However, it is believed that many of us violate this principle. The study conducted by Kahneman and Tversky (1984) where they asked their participants to make decision about the terrible disease which is expected to kill 600 people. The participants have been given two alternatives to the problem.
A) 200 people will be saved (72%)
B) There is a 1/3 probability that 600 people will be saved and 2/3 probability that no people will be saved (28%)
As I expected many of their participants preferred the option where 200 lives will be saved. Framing effects is well known in the financial sector, for example insurance companies, and there is also evidence that positive and negative framing effects are associated with different levels of cognitive processing. Dunegan (1993), study with international company engaged in developing high technology engineering systems suggested that the positive frames stated that of the project undertaken by the team, 30 of the last 50 have been successful and the negative frame stated that of the projects undertaken by this team, 20 of the last 50 have been unsuccessful. The negative framing group allocated less money on the project and they also were more concerned in reducing the costs. (Hardman, 2009)
The question is whether or not framing is a reliable phenomenon. a meta-analysis conducted by Kuhberger (1997) suggests that framing is reliable phenomenon, however, outcome salience manipulation, which constitute a considerable amount of work.
Thursday, 20 May 2010
Decision under risk and uncertainty (Utility measurement and Expected utility theory)
This week’s topic is very important because in our everyday life we are constantly making decision and many of these decisions involves certain risks. In most of day by day decision the probabilities are not known by the decision makers, which according to psychologists is known as decisions under risk and uncertainly. The academics normally express the uncertain events in numeral forms as odds probabilities and is quit difficult to assess the probability of an uncertain event or uncertain quantity. There are limited amount of heuristic principles, which reduces difficult tasks of assessing probabilities and values to a much simpler judgmental operations. However, even though these heuristics are useful they can sometimes lead to errors. Many risky decision making have taken a more quantitative approach and they assume that when individuals make a risky decision in reality what they are trying to do is maximise their expected value and expected utility. According to Hardman (2009), when it comes to expected value theory the probabilities and monetary problems can be determined by calculating the value of each possible outcome and weighting these outcomes by their probability of occurrence. On the other hand the expected theory the individuals are quite happy to pay a large sum of money due to the fact that there is an infinite expected value. Bernoulli (1954) suggested that individuals do not always behave as thought they are maximising expected value this is because while as a person’s wealth increases each extra unit of money adds utility but by less than the previous unit. It’s quite fascinating to learn that expected value theory believes that the rational decision maker should evaluate monetary outcomes by the probability of their occurrence, however, expected utility theory believes that rational decision maker should evaluate utilities of the outcomes by their probability of occurrence. The good thing about this theory (utility) is that it can be applied to other things rather than just money. However, the disadvantage is that it has not being measured directly and the neuroscience evaluation of the theory suggests that dopamine system responds to actual rewards and symbolic information (suggestion are based on human brain) (Hardman, 2009). Today I have learned that Utility and prospect theory do have things in common such as their integration and maximisation of something. Prospect theory is more concerned about the expectations rather than the monetary values. For example, if I have £10 in my pocket and someone promised to give me £100, however, she decided to give me £50 instead, which means that I am loosing because I expected to receive £100 from that person and I didn’t. Our reference point in prospect theory is our expected value. There is more explanation of the theory than evaluation. The graph below represents my utility function for money values ranging from £0 to £100,000
Fig 1
Although, the graph suggests risk aversion but i still consider myself rational because i was trying to maximise my expected utility.
Fig 2
I'm not really sure about the interpretation of the second graph but it seems almost perfect for risk taker.
Fig 1
Although, the graph suggests risk aversion but i still consider myself rational because i was trying to maximise my expected utility.
Fig 2
I'm not really sure about the interpretation of the second graph but it seems almost perfect for risk taker.
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