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Judgement [email protected]

Judgement [email protected]. Judgement We change our opinion of the likelihood of something in light of new information. Example: Do you think

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Page 1: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Judgement

[email protected]

Page 2: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

JudgementWe change our opinion of the likelihood of something in light of

new information.

Example: Do you think you did well on the exam?

Yeah, it was ok not to hard.

Friend says that he found it very hard.

You now believe that the exam might have been difficult.

Page 3: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Neglecting base rates Base rate information:

The frequency with which an event occurs.

People often fail to take base rates fully into account.

People do not use base rates in everyday judgements.

Base rates are not used when they are ambiguous, unreliable, or unstable.

Page 4: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Why do we neglect base rates?Representative heuristics

Events that are representative or typical of a class are assigned a high probability of occurrence.

This heuristic is used when people judge the probability that an object or event A belongs to a class or process B.

Example: You are given a description of an individual and are required to

estimate the probability that he/she has a certain occupation.

Estimate will be influenced by the similarity between the individual’s description and your stereotype of that occupation.

Page 5: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Kahneman and Tversky (1973) Jack is a 45 year old man. He is married and has four children.

He is generally conservative, careful, and ambitious. He shows no interest in political and social issues and spends most of his free time on his many hobbies which include sailing and mathematical puzzles.

Is this man an engineer or a lawyer?

Page 6: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Kahneman and Tversky (1973) Half the participants were told that the description was selected

at random from a pool of 100 descriptions and that: A) 70 were engineers B) 30 were lawyers

Or

A) 70 were lawyers B) 30 were engineers

Page 7: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Kahneman and Tversky (1973)Results:

.90 probability that Jack was an engineer

This was the same for the two groups

Regardless of the information given to them about the number of lawyers or engineers

Thus they did not take into account the base rate information

People focus on the description and on the match between the description and the occupation

Page 8: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Conjunction Fallacy Mistaken belief that the combination of two events (A & B) is

more likely than one of the two events alone.

More likely if the events are typical than atypical

Linda is a 31 years old, single, outspoken and very bright. She majored in philosopy. As a student, she was deeply concerned with issues of discrimination and social justice and also participated in anti-nuclear demonstrations.

Rank in order which occupation you believe Linda belongs to.

Page 9: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Conjunction Fallacy Three of the categories were:

Bank teller Feminist Bank teller and Feminist

Most people ranked bank teller and feminist more than bank teller or feminist alone.

Page 10: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Availability Heuristic Estimating the frequency of events on the basis of how easy or

difficult it is to retrieve relevant information from long-term memory.

If a word of three letters or more sampled at random from English text, is it more likely that the word starts with r or has r as its three letters?

Most participants argued that a word starting with r was more likely. words starting with r can be retrieved more easily from memory.

Page 11: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Numerosity Heuristic Over-inferring quantity

People generally eat less when food is divided into small pieces becuase it seems like there is more food.

We use this heuristic when the judging task is difficult.

Page 12: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Support Theory An event will appear more or less likely depending on how it is

described.

A more explicit description of an event will typically be regarded as having greater subjective probability than the same event described in less explicit terms.

Two reasons:

An explicit description draws attention to aspects of the event that are less obvious in the non-explicit description.

Memory limitations mean that people do not remember all of the relevant information if it is not supplied.

Page 13: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Support Theory Evidence (Johnson et al., 1993):

Participants were offered health insurance covering either: (a) hospitalisation for any reason or (b) for any disease or accident.

Those offers were the same, but participants payed more for when health insurance was offered for disease or accident (more explicit).

Page 14: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Recognition Heuristics If one of the two objects is recognised and the other is not

people choose the recognised object as having a higher value.

Which city has a bigger population Geelong or Lefkoşa?

Three components:

1. Search rule: search for name recognition & big landmarks to validate

2. Stop rule: Stop after finding a discriminatory cue

3. Decision rule: Choose outcome

Page 15: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Evaluation Outcome choosen could be due to the recognition heurstic but

could also be due to the person’s knowledge that the recognised city is larger. E.g., Is Melbourne a bigger city or Magusa?

Person needs to also consider whether the recognised city known to be small is larger than the unrecognised city. E.g., Is Girne a bigger city or Darwin?

Page 16: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Evaluation It is not clear why people often overlook information that is well

known to them.

How people decide which strategy to use has not been evaluated.

Page 17: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Decision Making Determined by rational factors on inferences and outcome

information as well as experienced and anticipated emotion.

The two key emotions are regret and fear.

People also make decisions based on social and cultural expectations.

Page 18: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Omission Bias Individual prefers inaction to action

To avoid loss due to their action

Disease kills 5 per 10, 1000

Vaccine has potential side effects

Most parents thus avoid vaccination to prevent side effects

Page 19: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Satisficing Used to make complex decisions

Involves choosing the first option meeting the individual’s minimum requirement.

Satisficers are happier and more optimistic than maximisers, they have greater life satisfaction and experience less regret and self blame.

Page 20: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Prospect Theory Person weighs the subjective values and losses and gains to

make a decision

Loss aversion:

People are much more sensitive to losses than gains

For example: Resort paid 100 dolars – became sick on the way

Most people would continue rather than turn back and go home

Because they would lose 100 dolars rather than gain comfort at home

Page 21: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Prospect Theory Risk Aversion:

Sure gain is chosen Would you like a sure gain of 800 dolars or 85% of gaining 1000

dolars 800 dolars chosen Avoid risky decisions

Risk Seeking: Sure loss of 800 dolars or 85% of losing 1000 dolars They chose option 2: risk losing 1000 dolars

Page 22: Judgement ilmiye.ozreis@emu.edu.tr. Judgement We change our opinion of the likelihood of something in light of new information. Example:  Do you think

Prospect Theory Self esteem affects whether we decide on risk aversions or risk

seeking.

Those with low self esteem are risk aversions as they would not want to damage their images further by incuring a potential risk.