FINAL EXAM

Question 1

Making decisions under conditions of uncertainty
Uncertainty: lacking knowledge about which events will occur

To make decisions under this condition requires that people estimate the probability that an event will occur

Answer 1

Probabilistic reasoning.

Question 2

Heuristics:

Answer 2

: informal, intuitive, speculative strategies for making a decision.
Makes decision-making more efficient but can lead to errors.

Question 3

evaluating the probability of an event by judging the ease with which relevant instances come to mind.

Answer 3

Availability heuristic:

Question 4

Evaluating the probability of an event In terms of how well it represents or matches a prototype

Answer 4

Representativeness heuristic:

Question 5

the relative proportion of different classes in the population.

Answer 5

is Base rates

Should rely on things with higher base rates.

Question 6

Conjunction rule:

Answer 6

Conjunction rule: the probability of a conjunction between two events can not be greater than the probability of one event alone.

Question 7

incorrect assumption that two+ specific conditions are more likely than one general condititon

Answer 7

Conjunction fallacy:

Question 8

Randomness.
It has clumpiness.
Contributes to the Gamblers fallacy.

Answer 8

Randomness.
It has clumpiness.
Contributes to the Gamblers fallacy.

Question 9

Gamblers fallacy:

Answer 9

the probability of a hit is a greater after a string of misses.
People are predisposed to try to impose patterns on random events.
Contributes to the hot hand fallacy.

Question 10

the probability of a hit is greater after a hit than after a miss.

Answer 10

Hot hand:

Question 11

The more times that you run an experiment, the closer the average of the results approximates the expected result.

Answer 11

Law of large numbers: 
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Also applies to literal experiments: the larger the number of individuals that are randomnly drawn from a population, the more representative that sample will be of the entire population.

Question 12

Expected utility Hypothesis.

Answer 12

According to Expected Utility Hypothesis, EU, decision making is based on an outcomes utility and the probability of it being achieved.

Question 13

EU=P x U
Probability: a person’s belief that an event will occur
Not an objective probability but instead is subjective.
Utility: the subjective value of an outcome
More valuable outcomes have greater utility; they produce great satisfaction.

Answer 13

EU=P x U
Probability: a person’s belief that an event will occur
Not an objective probability but instead is subjective.
Utility: the subjective value of an outcome
More valuable outcomes have greater utility; they produce great satisfaction.

Question 14

90% chance of winning 3k
EU=.9 x 3k= 2.7k
EU= .45 x 6k= 2.7k
45% chance of winning 6k

90% chance of losing 3k
EU=.9 x 3k= -2.7k
EU= .45 x 6k= -2.7k
45% chance of losing 6k

Notice The EU for gains is identical, the EU for losses is identical, but we show a definite preference for one outcome over another.
Our probabilistic reasoning is not objective.

Answer 14

90% chance of winning 3k
EU=.9 x 3k= 2.7k
EU= .45 x 6k= 2.7k
45% chance of winning 6k

90% chance of losing 3k
EU=.9 x 3k= -2.7k
EU= .45 x 6k= -2.7k
45% chance of losing 6k

Notice The EU for gains is identical, the EU for losses is identical, but we show a definite preference for one outcome over another.
Our probabilistic reasoning is not objective.

Question 15

Framing:

Answer 15

refers to the perspective from which an outcome is viewed.
An outcome can be viewed as achieving a gain or avoiding a loss.
How a choice is framed coupled with the probability of achieving the outcome determines a person’s decision.

Question 16

Framing and risk
90% chance is more of a sure thing than 45% which is more risky
Risk-averse: when fraimed as a gain, people are risk averse
Theyd rather take 90% chance over 45% chance of gaining money.
Risk-taking When framed as a loss, people are risk takers
Theyd rather take 45% chance over 90% chance of losing money
These findings also demonstrate that EU doesn’t explain human behavior well.

Answer 16

Framing and risk
90% chance is more of a sure thing than 45% which is more risky
Risk-averse: when fraimed as a gain, people are risk averse
Theyd rather take 90% chance over 45% chance of gaining money.
Risk-taking When framed as a loss, people are risk takers
Theyd rather take 45% chance over 90% chance of losing money
These findings also demonstrate that EU doesn’t explain human behavior well.

Question 17

The effects of framing
When an outcome is framed as a loss, we become risk takers in decision making

When an outcome is framed as a gain, we become risk averse in our decision making

Answer 17

The effects of framing
When an outcome is framed as a loss, we become risk takers in decision making

When an outcome is framed as a gain, we become risk averse in our decision making

Question 18

The effects of time.

Answer 18

Delay interval: time between the current behavior and the availability of the future outcome.
As a consequence of this delay, the outcome loses value.

Question 19

Delay discounting (aka temporal discounting) occurs when a future outcome is represented in the present at a marked-down value.

Answer 19

Delay discounting (aka temporal discounting) occurs when a future outcome is represented in the present at a marked-down value.

Question 20

Outcomes as losses and gains
Losses loom larger than gains
The loss of an outcome is more dissatisfying than the gain of that same outcome is satisfying
A loss 100 is more dissatisfying than a gain is satisfying.

Answer 20

Outcomes as losses and gains
Losses loom larger than gains
The loss of an outcome is more dissatisfying than the gain of that same outcome is satisfying
A loss 100 is more dissatisfying than a gain is satisfying.

Question 21

At the same outcome delay interval, the subject value of an outcome loss is greater than the subjective value of an outcome gain.

Answer 21

At the same outcome delay interval, the subject value of an outcome loss is greater than the subjective value of an outcome gain.

Question 22

People prefer larger outcomes over smaller outcomes

People prefer immediate over delayed outcomes.

Answer 22

People prefer larger outcomes over smaller outcomes

People prefer immediate over delayed outcomes.

Question 23

Preference reversal
When amount and delay interact: If the delay interval is long, we prefer the larger delayed outcome
As delay interval shortens, we shift preference to smaller immediate outcome.

Answer 23

Preference reversal
When amount and delay interact: If the delay interval is long, we prefer the larger delayed outcome
As delay interval shortens, we shift preference to smaller immediate outcome.

Question 24

The statistics don’t apply to the individual argument

Answer 24

Because people are unique, statistics don’t directly apply to anyone individually

Question 25

Clinical vs statistical approaches to decision-making.
Debate: How do the clinical versus statistical approaches to decision-making compare?

A major goal of science= predict outcomes.

Answer 25

Clinical vs statistical approaches to decision-making.
Debate: How do the clinical versus statistical approaches to decision-making compare?

A major goal of science= predict outcomes.

Question 26

Clinical = informal, impressionistic, intuitive decision-making strategy, may or may not reflect expertise.
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Statistical= actuarial, mechanical, formal, algorithmic, mathematical models based on quantitative data.

Answer 26

Clinical = informal, impressionistic, intuitive decision-making strategy, may or may not reflect expertise.
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Statistical= actuarial, mechanical, formal, algorithmic, mathematical models based on quantitative data.

Question 27

The statistical approach to decision-making tends to outperform the clinical approach in predicting what someone will do.
True even of experts
WHY?

People have biases, use heuristics, and encounter other common cognitive fallacies
Availability and representativeness
Confirmation bias.
Illusory correlations.
Statistical models don’t have these problems.

Answer 27

The statistical approach to decision-making tends to outperform the clinical approach in predicting what someone will do.
True even of experts
WHY?

People have biases, use heuristics, and encounter other common cognitive fallacies
Availability and representativeness
Confirmation bias.
Illusory correlations.
Statistical models don’t have these problems.

Question 28

People are bad at combining information, especially when phenomena are measured in different ways
Results in inaccurate decisions.
Statistical models can combine information more effectively.

Answer 28

People are bad at combining information, especially when phenomena are measured in different ways
Results in inaccurate decisions.
Statistical models can combine information more effectively.

Question 29

Student Z has a B+ in philosophy and is ranked 66th out of 100 in English

Half were asked what his grade may be and the other was asked rank in history class
One biased towards the previously mentioned grade and the other biased towards the rank.

Answer 29

Student Z has a B+ in philosophy and is ranked 66th out of 100 in English

Half were asked what his grade may be and the other was asked rank in history class
One biased towards the previously mentioned grade and the other biased towards the rank.

Question 30

Third Agreement within and between (expert) decision-makers.
Within: Does the decision-maker use a single decision strategy in every case.
Between: do multiple decision makers make similar decisions about the same cases?
Problem: if there are two different decisions about the same case, only one can be optimal

Given the same data on repeated occasions, statistical models generate identical decisions.

Answer 30

Third Agreement within and between (expert) decision-makers.
Within: Does the decision-maker use a single decision strategy in every case.
Between: do multiple decision makers make similar decisions about the same cases?
Problem: if there are two different decisions about the same case, only one can be optimal

Given the same data on repeated occasions, statistical models generate identical decisions.

Question 31

Judgmental Bootstrapping:

Answer 31

Judgmental Bootstrapping: The development of a statistical model that assimilates an experts forecasts into it by inferring rules the expert appeared to use in making the forecasts
Notice that expert’s judgement is used to create the model.

Question 32

Weighting of interrelated variables

In psych, many variables are interrelated eg types of intelligence.

Redundant information is weighted more heavily by human judges and less heavily by statistical models.

Statistical models weight unique models more heavily than redundant information.

Answer 32

Weighting of interrelated variables

In psych, many variables are interrelated eg types of intelligence.

Redundant information is weighted more heavily by human judges and less heavily by statistical models.

Statistical models weight unique models more heavily than redundant information.

Question 33

Are there any cases in which the clinical approach outperforms the statistical approach?

Answer 33

Broken leg case?
A prof goes to the movies on Tuesday nights.
Stat model predicts a 90 percent chance he goes to the movies.
Does not predict health stuff.
Prof a is in a hip cast that wont fit into the seats
The stat model doesn’t know this.
The clinician does.
This is why a personal evaluator can outperform the stat model.

Question 34

Why do we adhere to the clinical approach?

Answer 34

Deficits in understanding judgement fallacies.
Fear of replacement.
Belief in the efficacy of one’s judgement.
The “Dehumanizing” feel of statistical models, but:
The individual’s unique characteristics can be integrated into the statistical models.
The statistical models can be public and reviewed.

The good thing about these approaches is that they are not mutually exclusive.

Question 35

As you gain more information about reality, you will have to use your own clinical expertise to evaluate all the information that is given to you
From both clinical and statistical approaches.

Answer 35

As you gain more information about reality, you will have to use your own clinical expertise to evaluate all the information that is given to you
From both clinical and statistical approaches.

Question 36

The key to evaluating and synthesizing these kinds of information:

Answer 36

understanding where the information comes from and what it means.
There are limitations to what any one calculation can tell you.

Question 37

If I flip a coin 10 times, it is entirely possible that the flips lands on all heads.
However, if I flipped the coin 10k times, I would likely be close to a 50-50 split between heads and tails. This illustrates the:

Answer 37

Law of Large numbers.

Question 38

Given the same data on repeated occasions, which of the following is most likely to generate an identical decision:

Answer 38

A statistical model.

Question 39

1. The gamblers fallacy is__________

Answer 39

the probability of a hit is a greater after a string of misses.

Question 40

2. Framing refers to___________

Answer 40

c. the perspective from which an outcome is viewed.