phil of science

This class was created by Brainscape user Hendrik Diepers. Visit their profile to learn more about the creator.

Decks in this class (43)

lecture 1
Five sources of evidence,
Intellectually arrogant,
An illusion of understanding
15  cards
Lecture 2
What is the point of saying that ...,
Does calling something science ma...,
Non scientific practices
20  cards
book chapter 1
Philosophers have traditionally t...,
Knowledge,
Knowledge requires
18  cards
book chapter 1 (2)
Two cautionary notes about falsif...,
Two key elements of falsification...,
Evidence
10  cards
book chapter 1 (3)
Normative claim,
Descriptive claim,
Confirmation bias
21  cards
book chapter 2 (1)
Three common ingredients in recip...,
Experiment,
Variable
19  cards
book chapter 2 (2)
Perfectly controlled experiment,
Operational definition,
Clustor indicators
16  cards
book chapter 2 (3)
When are non experimental studies...,
Laboratory experiments,
When does an experiment have inte...
21  cards
book chapter 2 (1,2)
Auxilary assumptions,
Replication,
Physical constraints
5  cards
lecture 3 (1)
Constructing an experiment three ...,
Better can vary depending on the ...,
Experiments provide
6  cards
Lecture 3 (2)
0  cards
lecture 4 (1)
What are data driven studies good...,
Classification,
Prediction
18  cards
chapter 3 (1)
What is the bay model,
Target system or target,
Why cant you always build identic...
11  cards
Chapter 3 (2)
Data model,
Data cleansing,
Data models are used
10  cards
chapter 3 (3)
Isomorphism,
Abstraction,
Idealization
12  cards
lecture 5
What is a model,
A good model balances abstraction...,
Looking at a concrete model baymodel
19  cards
lecture 5 (1)
0  cards
chapter 4 (1)
Reasoning,
System 1,
System 2
18  cards
chapter 4 (2)
Hypothesis testing requires at le...,
Empirical evidenc eis the
8  cards
chapter 4 (1.2)
Any deductive inference is either,
Monotonicity,
Affirming the antecedent of a con...
13  cards
chapter 8 (1)
Transaction exposure,
Transaction exposure,
Economic exposure
11  cards
chapter 8 (2)
0  cards
lecture 6
How to find counterexamples to hy...,
What is logic,
What is an argument
13  cards
lecture 6 (1)
0  cards
lecture 7
Fact non deductive inductive reso...,
Two main types of inductive reaso...,
Generalization
14  cards
lecture 7 (1)
Upshots,
Abductive reasoning or inference ...,
Example of abductive reasoning fr...
6  cards
probability theorys paper (lecture 7)
1  cards
lecture 8
Thee kinds of probability,
Epistemic,
Objective
16  cards
lecture 8 (2)
Frequency interpretation of proba...,
What is a long sequence of trials,
One problem frequency interpretation
8  cards
chapter 6.1
Descriptive statistics,
Inferencial statistics,
Requency distribution
18  cards
chapter 6.2
Null hypothesis,
Alternative hypothesis,
The nulll hypothesis and alternat...
16  cards
lecture 9
Ways statistical tools can fool us,
What is statistics good for despi...,
Hypothesis testing the nhst way
14  cards
chapter 6.3
Classical statistics,
Problems with p values,
Second problem with classical sta...
8  cards
lecture 10
The problems with nhst,
Bayesian statistics steps,
Basic ideas baesian stats
12  cards
lecture 11
Why bother about causation,
Philosophers have typically worri...,
What is causality
19  cards
chapter 7.1
Proximate causes,
Distal causes,
Common cause
11  cards
chapter 7.2
Millls method of concomitant vari...,
Method of agreement,
Method of difference
6  cards
lecture 7.3
Self explanation effect,
Understanding,
Illusion of explanatory depth
11  cards
chapter 8.1
Self explanation effect,
Understanding,
Illusion of explanatory depth
5  cards
chapter 8.2
Scientific theories,
The most significant scientific b...,
Scientific revolution
9  cards
chapter 8.3
Matilda effect,
Value free ideal for science,
Some challenges to the value free...
7  cards
lecture 12
The deductive nomological account...,
The deductive nomological account...,
Psychologists use two general ten...
23  cards
lecture 13
Three facts,
The value free ideal,
Social values
12  cards

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phil of science

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