Summary Studyquestions Applied Research Methods D&H

Study questions
Applied Research Methods - D&H
Lecture 1
• Which types of research can be conducted with observations, correlations, and
experiments, respectively?
 Observations: finding phenomena
 Correlations: relationships
 Experiments: causal explanations


• What is meant by the precision of a theory?
The theory that predicts more precise than the other is better.
 When a theory is precise it is easier to be wrong, but it tells us more if it is right.


• What is meant by the parsimony of a theory?
A theory that makes just a few assumptions to predict something is better than a very
complicated theory that makes a lot of assumptions to predict a phenomena. Counts if both
theories have the same precision.
A theory that makes just a few assumptions to predict something is better than a very
complicated theory that makes a lot of assumptions to predict a phenomena. Counts if both
theories have the same precision.
A theory that makes just a few assumptions to predict something is better than a very
complicated theory that makes a lot of assumptions to predict a phenomena. Counts if both
theories have the same precision.
 Easier theories are better than complicated ones.


• Why are testability and falsifiability considered important features of a theory?
Testability: theory can only be good, when it can be tested.
Falsifiability: theory can only be good, when it can be wrong.
 Theories are useless if they could explain everything. Theory must make predictions
that can be wrong.
 Otherwise, we cannot distinguish science from pseudoscience, and we cannot compare
studies based on their degree of falsifiability.


• What is the internal validity of a study?
Did the intervention cause the results? (and not a confounded variable)


• What is the external validity of a study?


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,How far can the results be generalized?


• What is the construct validity of a study?
Which aspect of the intervention caused the results?
Manipulation. Which aspects are important?
The extent to which variables measure what they are supposed to measure.


• What is the statistical validity of a study?
Are the statistical conclusions correct?


• How can correlations be used and interpreted?
Correlation: direction and size (how closely are 2 variables related)
Regression: prediction (how can I predict one variable if I know the other.




• How can correlations not be interpreted?
 Not as an explanation of ‘why’ or causality.
 The direction of the relation is unclear. There can be some third variables.
 Beware of causal interpretations: correlation is necessary, but not sufficient prediction
for causation.
 When one event is before another, you still not can say that this is causation. You need
an experiment for this.


• Does correlation imply causality? If yes, why? If not, why not?
No, correlation between 2 variables simply indicates that a relationship exist. Whereas
causation is more specific and says that one event actually causes the other. Correlation does
not necessary mean that the one effect the other, there is only a connection.
 If causality, then correlation
 But not: if correlation, then causality


• How does the temporal order of two variables help to establish a causal relation
between them?
Even if 2 variables are both correlated and temporally ordered, the earlier one does not have
to be the cause of the later one.
There is an experiment needed.



2

, In an experiment: the independent variable must occur first in time to influence the dependent
variable.


• What do you have to do to test whether two variables are causally related?
Experiment -> (randomization, manipulation of the independent variable)
Temporal order, alternative explanations.


• What are independent, dependent, and control variables of experiments?
- Independent: this is manipulated.
- Dependent: this is measured.
- Control variables: when not controlled, this are confounding variables.


• What does it mean if an experimental independent variable is a between-subjects
variable?
- Different groups, get different level of variable.
- Every subject experiences only one level of the independent variable.
- Randomization to groups.


• What does it mean if an experimental independent variable is a within-subjects
variable?
Every subject experiences every level of the independent variable.


• What are advantages and disadvantages of between-subjects and within-subjects
experimental designs?
 Within:
+ requires fewer participants.
+ Easier to find effects.
- But there can be an order-effect.
 Between:
+ minimize the learning effect, lead to shorter sessions.
+ Also no confounding variables.
- But you need a big sample to have good randomization.


• What is random assignment, and why is it so very important?
- 1 control group and 1 or more experimental groups.
- Ensure that the groups are comparable.
- Avoiding confounding variables.

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