Applied research methods (D&H): All study questions
Lecture 1
General topics
• Which types of research can be conducted with observations, correlations, and
experiments, respectively?
o Observations: finding phenomena
o Correlations and quasi-experiments: finding relationships
o Experiments: finding causal explanations
o All of them: developing and testing theories of experience and behavior
• What is meant by the precision of a theory? Predictions in a theory need to be as specific as
possible (better quality), e.g., clearly formulating which observations are predicted and which
would falsify them
• What is meant by the parsimony of a theory? Simplicity, as few assumptions as possible
(better quality)
• Why are testability and falsifiability considered important features of a theory? Theory
needs to be testable because otherwise it’s only an assumption. And falsifiability because
otherwise a theory can’t be proved otherwise/wrong, there needs to be room for other
better theories in case the observation contradicts the theory
• What is the internal validity of a study? Are the results there because of the intervention
(independent variable) (and not because of confounds)?
• What is the external validity of a study? It tells us to what extend the results can be
generalized
• What is the construct validity of a study? It tells us if the results of your research truly are an
indication of the construct you want to make a statement about
• What is the statistical validity of a study? It tells us if the statistical conclusions are correct
• How can correlations be used and interpreted? To what extend two variables are related to
each other, the size and the direction
• How can correlations not be interpreted? As causal relationships
• Does correlation imply causality? If yes, why? If not, why not? No, it only tells us something
about the direction and size of the relationship, nothing about the origin
• Does causality imply correlation? If yes, why? If not, why not? Yes, correlation is a condition
for causality
• How does the temporal order of two variables help to establish a causal relation between
them? It doesn’t
• What do you have to do to test whether two variables are causally related? Conduct an
experiment
, • What are independent, dependent, and control variables of experiments?
o Independent: the variable that is manipulated in the experiment, hypothesized that
this is the causing variable
o Dependent: hypothesized to be affected by the independent variable, this variable is
measured
o Control: constant variable, controlled in the experiment, control group will be
compared to the experimental group
• What does it mean if an experimental independent variable is a between-subjects
variable? Then there are multiple levels of the independent variable and independent
groups, every subject experiences only one level of the independent variable. The groups are
compared to each other
• What does it mean if an experimental independent variable is a within-subjects variable?
There are multiple levels of the independent variable, each subject experiences every level of
the independent variable. The subjects are compared to themselves at each level.
• What are advantages and disadvantages of between-subjects and within-subjects
experimental designs?
o Between subjects
Advantage: randomization
Disadvantage: no direct comparison per participant
o Within subjects
Advantage: direct comparison per participant
Disadvantage: there could emerge order effects
• What is random assignment, and why is it so very important? Every subject is randomly
assigned to a group, this excludes confounds. Diffrences between groups are the result of
random factors, so you can assume that the groups don’t differ from each other. The results
can be better generalised
• What is the difference between a quasi-experiment and a real experiment? In a quasi-
experiment no randomization takes place, so it’s a correlational study, not a causal one
Statistical Power
• In statistical testing, what is the alpha error? A significant effect is found in the sample even
though it’s really non-existent in the population (false positive). So a 0-hypothesis is being
rejected even though it shouldn’t
• In statistical testing, what is the beta error? There is no significant effect found in the
sample even though there really is an existing effect in the population (false negative). So a
0-hypothesis is accepted even though it shouldn’t
• What does the term "effect size" mean? How large is a difference / correlation /
relationship?
• What does the term "statistical power" mean? What the probability is that this effect will be
statistically significant in an experiment. So the probability of correctly rejecting the 0-
hypothesis
Lecture 1
General topics
• Which types of research can be conducted with observations, correlations, and
experiments, respectively?
o Observations: finding phenomena
o Correlations and quasi-experiments: finding relationships
o Experiments: finding causal explanations
o All of them: developing and testing theories of experience and behavior
• What is meant by the precision of a theory? Predictions in a theory need to be as specific as
possible (better quality), e.g., clearly formulating which observations are predicted and which
would falsify them
• What is meant by the parsimony of a theory? Simplicity, as few assumptions as possible
(better quality)
• Why are testability and falsifiability considered important features of a theory? Theory
needs to be testable because otherwise it’s only an assumption. And falsifiability because
otherwise a theory can’t be proved otherwise/wrong, there needs to be room for other
better theories in case the observation contradicts the theory
• What is the internal validity of a study? Are the results there because of the intervention
(independent variable) (and not because of confounds)?
• What is the external validity of a study? It tells us to what extend the results can be
generalized
• What is the construct validity of a study? It tells us if the results of your research truly are an
indication of the construct you want to make a statement about
• What is the statistical validity of a study? It tells us if the statistical conclusions are correct
• How can correlations be used and interpreted? To what extend two variables are related to
each other, the size and the direction
• How can correlations not be interpreted? As causal relationships
• Does correlation imply causality? If yes, why? If not, why not? No, it only tells us something
about the direction and size of the relationship, nothing about the origin
• Does causality imply correlation? If yes, why? If not, why not? Yes, correlation is a condition
for causality
• How does the temporal order of two variables help to establish a causal relation between
them? It doesn’t
• What do you have to do to test whether two variables are causally related? Conduct an
experiment
, • What are independent, dependent, and control variables of experiments?
o Independent: the variable that is manipulated in the experiment, hypothesized that
this is the causing variable
o Dependent: hypothesized to be affected by the independent variable, this variable is
measured
o Control: constant variable, controlled in the experiment, control group will be
compared to the experimental group
• What does it mean if an experimental independent variable is a between-subjects
variable? Then there are multiple levels of the independent variable and independent
groups, every subject experiences only one level of the independent variable. The groups are
compared to each other
• What does it mean if an experimental independent variable is a within-subjects variable?
There are multiple levels of the independent variable, each subject experiences every level of
the independent variable. The subjects are compared to themselves at each level.
• What are advantages and disadvantages of between-subjects and within-subjects
experimental designs?
o Between subjects
Advantage: randomization
Disadvantage: no direct comparison per participant
o Within subjects
Advantage: direct comparison per participant
Disadvantage: there could emerge order effects
• What is random assignment, and why is it so very important? Every subject is randomly
assigned to a group, this excludes confounds. Diffrences between groups are the result of
random factors, so you can assume that the groups don’t differ from each other. The results
can be better generalised
• What is the difference between a quasi-experiment and a real experiment? In a quasi-
experiment no randomization takes place, so it’s a correlational study, not a causal one
Statistical Power
• In statistical testing, what is the alpha error? A significant effect is found in the sample even
though it’s really non-existent in the population (false positive). So a 0-hypothesis is being
rejected even though it shouldn’t
• In statistical testing, what is the beta error? There is no significant effect found in the
sample even though there really is an existing effect in the population (false negative). So a
0-hypothesis is accepted even though it shouldn’t
• What does the term "effect size" mean? How large is a difference / correlation /
relationship?
• What does the term "statistical power" mean? What the probability is that this effect will be
statistically significant in an experiment. So the probability of correctly rejecting the 0-
hypothesis
