Notes from the video lectures of the Amsterdam University MOOC - Quantitative Research Methods, and the tutorials of the course: Research Methods and Design at Erasmus University College. Useful for most quantitative research courses, but specifically made for university college.
Scientific method – research is:
1. Empirically testable (possible to collect data)
2. Replicable (possible to test more than once, so no moon samples)
3. Objective (researcher isn’t biased, could be done by anyone)
4. Transparent (method is clear, everything is made public)
5. Falsifiable (evidence can disprove the theory)
6. Logically consistent (sound reasoning)
NOT: opinions, flawed or biased logic and observations
Scientific claims
Observations: don’t explain, just state
Hypothesis: describes pattern or general relation between things
Law: very precise and well supported hypothesis that is often mathematically
supported
Theory: broad overarching explanation of many related phenomena (consists of
many tested hypothesis)
Types of research:
Universalistic -> general explanation in all groups and societies
Particularistic -> explanation for particular phenomenon in a specific group, place
and time
Applied -> to improve human condition, explicitly solving a problem
Fundamental -> further our understanding of the world around us, to gain
knowledge
Fundamental = often universalistic
Applied = often particularistic
But not always!
Empirical cycle
Induction = if it happens once, will it happen all the time? Make a general rule
from observations
, Deduction = this is my general hypothesis, will it apply in new situations?
Predictions are formed
Testing hypothesis
Confirmation can never be conclusive: NO SCIENTIFICAL CLAIM CAN EVER BE
PROVEN
All we can do is provide overwhelming support
Disconfirmation CAN reject a hypothesis, but more often than not the explanation
can be a faulty method. Also, minor changes to the hypothesis happen more
often than complete rejection.
Criteria for evaluation
1. Reliability = the ability to SUCCESFULLY replicate the results
2. Validity
a. Construct (did the methods actually test the hypothesis, and are the
results manipulated accurately)
b. Internal validity (the observed effect is actually CAUSED by the
hypothesized cause)
c. External validity (will it hold in other settings?)
Causality
Hume said:
1. Cause and effect have to be connected (happen at the same time and
place)
2. Cause has to precede the effect
3. Cause and effect occur together consistently (if C -> always E etc.)
4. NO ALTERNATIVE EXPLANATIONS POSSIBLE
Correlation =/= causation!
Week 2 – Internal validity and variables
Internal validity = conclusions that are drawn based on the results that may not
are not caused by the intended cause
‘Anything other than the experimental stimulus that can affect the dependent
variable’
TYPES
History = (historical) events that happens during the experiment (something
goes wrong)
Maturation = do people grow wiser and older naturally? Do people get tired? Etc.
An effect caused by natural change
Testing = more sensitive to the second test, pretest influences the outcome of
the posttest
Instrumentation = something wrong with the test, is it always equally sensitive?
Is the tester always equally capable
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