Psych Slides Flashcards
Standard Beliefs
- People make rational assessments of probabilities based on all available information
- people use bayes rule
-have a normative viewpoint.
Monty Hall Problem. Switch Why or why not?
Monty hall problem is an example of why and how estimating conditional probabilities on the fly is difficult in its nature. If the judge flips one of the doors that will not be the car sticking with your original choice gives you a 1/3 chance as the judge will not flip over the car. Where if you switch you have a 2/3 probability as you get the benefit of choosing both the door flipped and the other door. So it is in your best interest to switch.
Taxi Cab Problem:
A cab was involved in a hit and run accident at night. Two cab companies,
the Green and the Blue, operate in the city. 85% of the cabs in the city are
Green and 15% are Blue. A witness identified the cab as Blue. The court
tested the reliability of the witness and concluded that the witness correctly
identifies each of the two colors 80% of the time. What is the probability
that the cab involved in the accident was Blue rather than Green?
This is a usage of Bayes rule. Should yield 0.41.
Linda is a 31 yo woman who is single, bright, and outspoken.
She also majored in philosophy. As a Student she was concerned with issues of social justice. What is more likely: Bank Teller or Feminist Bank Teller.
- First off Bayes Rule says: p(AlB)= (P(BlA) * P(A))/(P(B))
- So given this the odds ratio of this will be defined as:
(P(AlB)/P(-A/B))= (P(B l A)/P(B l -A))* (P(A)/(P(-A)) - People put a lot of emphasis on the first term on how representative B is of A and not enough on the base rates (2nd Term)
- This is due to the representative types coming to mind quicker and due to availability are over weighted due to their bigger role in our memory.
Intuition: What is the Probability you are red-headed if you are Irish?
Using the odds ratio:
(P(RH l Irish)/(P(Irish l Not RH) = (P(Irish l RH)/ P(Irish l Not Red Head) * P(RH)/ P(Not RH)
-People place too much emphasis on the first term: Being red headed is highly representative of being from Ireland and not enough emphasis on the 2nd term being red headed in Ireland is still uncommon (10%)
Law of Small Numbers
- People believe that true distribution is reflected in small samples
- Confidence should be derived based on the size of the sample.
- tend to over-extrapolate recent trends. When we know the model we get a gamblers fallacy effect
Gamblers Fallacy
The belief that in a string of independent random events a run of one outcome makes the opposite outcome “due” although the underlying probability does not change
Non-belief in the Law of Large Numbers
Tendency to treat short term data to reveal the long term probability of an outcome leading to “hot hand” beliefs instead of recognizing that large samples are needed for an accurate representation of accuracy.
Availability Heuristic
Biases probability towards events that are easier to recall or that are reported on often (eg: Shark attack or Murders) Those events are more at front of mind and come to mind more easily than more probable but less memorable other options such as how coconuts are more deadly than shark attacks yearly.
Attention
- Attention is limited
- We are only able to retain and pay attention to a small percent of our conscious experience
- Strong influence on our belief structure
Relative Thinking
- Value is usually compared relatively to the market
- we don’t usually rely on fundamentals but compare to each other
- Movie Theatre popcorn S; 3 M;5 L;6 makes the large look like the best option and a relatively good deal.
Partial Equilibrium Thinking
Analyzing the direct effect of a policy on one variable while holding all else constant not thinking about feedback loops and what would happen:
- Ex: Tariffs: Make foreign goods more expensive and improve US job creation. (What about consumer spending and retaliatory measures against US goods)
Anchoring
- Initial piece of information impacts the repsonse to another stimuli
- for example if you were asked the first two of your social security number then the number of countries in Africa your guess would be pulled closer to your first answer.
Priming
Exposure to a stimuli can influence the response to another stimuli. For example holding a hot beverage makes you more positive and happy.
Motivated Beliefs
- We choose beliefs that make us happy (we gain happiness from anticipating things called anticipation utility)
- We modify our beliefs to make ourselves happier
-Optimism Bias
Optimism Bias
Individuals report they are less likely to experience bad events and more likely to experience good events.
Cost of Motivated Beliefs
We have to convince ourselves something is possible or realistic, higher from the truth means a higher mental cost. we don’t want to make choices that will hamper out future consumption.
Horizon Bias
More optimistic with long term horizons for GDP growth earnings etc. Long term horizons are more easily manipulated towards motivated beliefs since they are more uncertain. Avoid disapointment and adjust beliefs closer to when the time comes.
Cognitive dissonance
The discomfort one feels when we take an action that conflicts with our positive self image. To avoid the feeling of discomfort we often manipulate our beliefs. Ex: Smoking
Memory
- Memory is associative and memories similar to the present cues are more likely to be recalled.
- Retrieved experiences simulate a distribution of future returns
-Recent and salient experiences are more likely to come to mind - Selective memory could be a way to maintain motivated beliefs: Positive feedback is remembered for a longer period than negative feedback
Confirmation bias
- Seek, interpret and remember information that supports what we already believe while discounting or ignoring evidence that contradicts it
- Driven by motivated beliefs and memory
- Prior biased inference is an important subset that plays into how we interpret data and information
Affective Feeling
A happier mood caused by external Stimuli leading to a more positive judgement about unrelated future outcomes
Cognitive Feelings
Easier to process and like things that look familiar or like you. Ex: Connection between how dogs look and their owners.
Trust
The belief that you will find what is desired in another rather than what is feared
Conformity
- Adjust beliefs, judgements and behaviors so they align with the perceived norms or actions of a group to gain social acceptance or because the group is viewed as a source of good information.
Groupthink
Group cohesiveness is more important than considering the facts.
Only works when ( the group is attractive and valued, isolated from other opinions, a strong vocal leader, stressful situation, and no process for considering other viewpoints)
Dissentions are rare and opposing ideas are stereotyped
Cognitive Noise
There is a cognitive noise when we form beliefs on valuations. This is due to cognitive constraints as there is a complex task at hand. They are aware of the noise and trend towards the default. Lessened when told the distribution than when you form your own beliefs.
Fundamental Attribution Error
People put more weight onto personality over environment although psychology says both matter.
Traditional Preferences
Happiness (utility) is a function of consumption or wealth. Exponential time discounting. Agent is risk adverse
Prospect Theory
-Carriers of value are losses and gains not final wealth levels
-Loss aversion: More sensitive to losses than gains
-risk adverse in gains risk taking in losses
-transform probabilities with a weighting function that applies high decision weight to low probability outcomes.
Realization Utility
Happiness from realization of a gain and disutility from a loss. paper vs realized gains and losses.
Altruism
Preference for increasing someone else’s’ utility even if it decreases your own material payoff.
Positive Reciprocity
Prosocial response where an individual responds to a kind action with another kind action
Negative Reciprocity
Retaliatory negative response even at a personal cost
Ellsberg Paradox
Ambiguity aversion is shown here as we like to know and understand the full distribution of an action
Efficient Coding
More resources are allocated to frequently seen stimuli
Time Discounting
Right now over any time in the future
It seems to be devoid of time and rationale unable to be explained by hyperbolic models. Shown by the marshmallow test
