The likelihood of an outcome represented by the extent to which available evidence points to the outcome.

Likelihood (Bayesian Inference)

Commonly referred to as the prior, it is the prior probability of an outcome occurring, represented by our initial belief about the probability of an outcome.

Prior Probability (Bayesian Inference)

Bayesian networks were developed to understand reasoning under conditions of uncertainty. It is based on Bayes Theorem and is a probabilistic model that represents a set of variables and their conditional dependencies by being able to find the probability of facts being true/false given already defined facts. A Bayesian network is represented by a directed acyclic graph which helps to visualize the probabilistic model for reviewing relationships between random variables and reasonings for causal probabilities given certain facts



Bayesian Networks

Updating your beliefs can be boring or uncomfortable but it very beneficial in the long run. Look for subtle signals in noise and avoid wishful thinking. The world doesn't work the way we want it so ideally we would behave like rational Bayesian updaters.

Update your Beliefs

Bayesian inference derives the posterior probability based on a prior probability and a likelihood function according to Bayes' theorem. $$P(C|D)=\frac{P(D|C)P(C)}{P(D)}$$ Here, the probability $$P(D|C)$$ is the likelihood function, and $$P(C)$$ is the prior probability.

Bayesian Inference Formula

Created by Thomas Bayes, who posited that our estimate of the probability of an outcome was determined by two things:
- 1) prior probability of an outcome 
- 2) likelihood of an outcome

University of Michigan - Ann Arbor

- Reaction time
- Levels of analysis
- Principle of Neural Representation
- Processing in perception
- Bayesian Inference
- Mental imagery

Focuses of Research on Perception

Goldstein, E. B. (2014). Cognitive psychology: Connecting mind, research and everyday experience. Nelson Education.


Cognitive psychology: Connecting mind, research and everyday experience

How long it takes to respond to a stimulus

Reaction time

A lot of what someone experiences is not based on direct stimuli, rather representations in the nervous system

Principle of Neural representation

Processing in perception

The ability to (mentally) recreate the sensory world in the absence of external stimuli. People can imagine tastes, smells and experiences

Mental Imagery

The study of perception involves multiple levels of analysis, extending from fundamental biological mechanisms to behavioral outcomes. These levels include:
1) Chemical processes
2) Activation of individual neurons
3) Activation of specific brain structures
4) Activation of interacting groups of brain structures
5) The conscious experience of perception
6) The resulting behavioral output or action

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