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jude duarte
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Decks in this class (27)
M1 - Epistemology
What is epistemology 1,
3 aspects of epistemology 2,
History of navigation 3
6
cards
M1 - Empiricism
Why does empiricism exist 1,
Empiricism 2,
Why is empiricism important 3
7
cards
M1 - Induction vc Deduction
Induction 1,
Example of induction 1 2,
Example of induction 2 3
8
cards
M1 - Parsimony/Occam's razor
Occams razor 1,
Parsimony 2,
Example of parsimony 3
6
cards
M1 - Falsifiability
Falsifiability 1,
What is falsifiability the practi...,
What has falsifiability given ris...
4
cards
M1 - Confirmation Bias
Confirmation bias 1,
Example of confirmation bias 2,
Theory dependence of observation 3
4
cards
M1 - Cultural Knowledge
Cultural observation knowledge 1,
Aboriginal cultural knowledge ind...,
Aboriginal cultural knowledge bac...
12
cards
M1 - Paradigm Shift
Paradigm shifts 1,
Example of paradigm shift 2
2
cards
M1 - Influences on scientific thinking
Economic influences 1,
Political influences 2,
Examples of political influences 3
5
cards
M1 - Ethics
Ethical research 1,
Ethical frameworks 2,
Ethical frameworks autonomy 3
23
cards
M2 - Literature search
Reason for an initial literature ...
1
cards
M2 - Research question
A research question should be 1,
Types of questions factual 2,
Types of questions comparative 3
7
cards
M2 - Hypothesis
Hypothesis 1,
Sign of good research question 2,
Signs of good hypothesis 3
3
cards
M2 - Evaluating resources
0
cards
M2 - Research Proposal
Detailed literature review 1,
What does a research proposal ide...,
Final scientific hypothesis 3
8
cards
M2 - Error
Error 1,
Random errors 2,
Systematic errors 3
4
cards
M2 - Error in uncertainty and curves of best fit
Uncertainty 1,
How is uncertainty represented 2,
Mass g uncertainty 3
18
cards
M2 - Quantitative vc Qualitative research
Qualitative categorical 1,
Quantitative 2,
Qualitative data types 3
28
cards
M2 - Large Data Sets
Large data sets 1,
Remote sensing 2,
Streamed data 3
3
cards
M2 - Data collection
0
cards
M2 - Creating an experiment together
0
cards
M2 - Impact of making data sets public
0
cards
M3 - Data, Evidence and Analysis Methods
0
cards
M3 - Graphical representations
0
cards
M3 - Relevance, accuracy, validity and limitations of data and its analysis
0
cards
M3 - Performance Measures (accuracy, precision, error, bias, data cleansing)
Performance measures 1,
Accuracy 2,
How is accuracy measured 3
5
cards
processing data for analysis
Methods of data processing 1,
Why is processing of data importa...,
Types of processed data 3
11
cards
More about
Sci Ext
- Class purpose General learning
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