Lecture 004

Topic 1: Explanation, Prediction, and the Aims or Goals of Science


Explanation as Deducing From Law: Apply Function

Carl Hempel: a deduction from the laws (of nature) that apply and the specific initial condition of the world surrounding the phenomenon to be explained.

Explanation as Description: More fine grained

Explanation: both compression of former data and prediction

Explanation as Specifying Causal Mechanisms

Explanation has causal relationship


Goal for science


Prediction: you don't need an explanation for prediction Prediction vs. Explanation


Qualifying potential causation variable

Topic 2: Scientific Representations

representation: partial, abstract

extra-mental representations:

Topic 3: The Nature of Scientific Theories - Realism and Anti-Realism (Reality and Generalization)



realists: theories are real because

anti-realist (instrumentalists): talking about measurements (theory) is not real


realists: bigger generalization, we can use representation variable to infer represented variable

anti-realist: all you have is data


  1. description vs. explanation A scientific description is a compressed representation of the natural phenomenon. Such a description is intended for better communication of ideas between scientists. A scientific explanation is both a compressed representation of the natural phenomenon and a causal relationship between all variables in the explanation. For example, in the case of "water changing from a liquid to ice", a scientific description may be: "At -12 Celsius under 1 atm, we observe that water molecules start to line up in a relatively stable pattern". A scientific explanation may be: "water molecules start to line up in a relatively stable pattern because they are at -12 Celsius under 1 atm." Notice how a description cannot be directly used as a prediction since it does not imply any relationship (other than that two phenomenons, temperature and the change in molecular structure, are happening at the same time) between temperature and patterns of water molecules. An explanation, however, can imply a causation relationship between variables. Because a scientific explanation is "a) something that describes that phenomenon in terms that we already understand or b) in terms that are more “fundamental” or c) in terms of the causes of the phenomenon" ("Topic 1: Explanation, Prediction, and the Aims or Goals of Science"), therefore an explanation contains a description (by a) and differs from a description because it has extra causation relationship (by b and c).

  2. correlation vs. causation in accuracy of prediction (using big data in stock market vs. provide an explanation, however, in my opinion there isn't a sound explanation to be provided) Because causation

  3. covaries with the effect (covariant)

  4. is similar to the effect in terms of duration, magnitude, and physical characteristics

therefore the relationship is more stable than a prediction

  1. science's purpose: prediction or explanation Since explanation has causality, it includes prediction. Then science is about explanation since it is boarder.

  2. Right or wrong: we cannot accurately know what's in other people's mind objective: come to same conclusion given the same premise subjective: come to different conclusion given the same premise

color blink:

DISAGREE: For this question, lets define "same" as an equivalence relationship on "inter-mental representation" as the average of all relevant "extra-mental representation". (learned from NLP)

My answer: There exists universal pattern, we can only approximate them. (This question is highly opinionated, therefore I don't have a valid justification for it.)

Class Notes

causal process: a process that has the ability to cause a persisting change in the structure of another process

causal interaction: is an intersection between two causal processes that changes the structure of both

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