Study Questions for Lecture 1 (Rinck)
General Topics
1. Which types of research can be conducted with observations, correlations, and
experiments,respectively=
Observations: finding phenomen
Correlations: finding relations
Experiments: finding casual
2. What is meant by the precision of a theory?
The accuracy also with multiple measures, the precision with which it can explain something
3. What is meant by the parsimony of a theory?
Should use less assumptions as possible to explain something
4. Why are testability and falsifiability considered important features of a theory?
A theory needs to be disproven otherwise it is not usefull and therefore it needs to be
tested.
5. What is the internal validity of a study?
Does it measure what it is supposed to measure? Does the intervention causes the effect?
6. What is the external validity of a study?
Is it generalizable?
7. What is the construct validity of a study?
Does it measure what it is supposed to measure? Does the test measures the construct?
8. What is the statistical validity of a study?
Is it stastically correct?
9. How can correlations be used and interpreted?
As an relationship between two variables and its strength and direction between these two.
10. How can correlations not be interpreted?
As an causal effect
11. Does correlation imply causality? If yes, why? If not, why not?
No because it means that there is a relationship between the variables and not perse an
causal relationship
12. Does causality imply correlation? If yes, why? If not, why not?
Yes because if there is a causal relationship between the variables, then there is a relation.
13. How does the temporal order of two variables help to establish a causal relation between them?
Helps to determine the causal relationship
If A comes before B then A could be the cause of B, but when B comes before A then A
cannot be the cause of B.
14. What do you have to do to test whether two variables are causally related?
Experiment with manipulation and randomization
15. What are independent, dependent, and control variables of experiments?
IV= manipulated
DV = measured
Control = constant
16. What does it mean if an experimental independent variable is a between-subjects variable?
Each subject gets 1 condition, one measure
17. What does it mean if an experimental independent variable is a within-subjects variable?
Each subject gets every condition, multiple measure.s
, 18. What are advantages and disadvantages of between-subjects and within-subjects experimental
designs?
BS: voordeel is dat je geen order effecten krijgt maar wel veen deelnemers nodig
WS: voordeel: weinig deelnmemers maar je hebt kans op order effecten
19. What is random assignment, and why is it so very important?
Important to assure that possible confounders are ecually distributed between the
conditions
20. What is the difference between a quasi-experiment and a real experiment?
Quasi heft manipulatie maar geen randomisatie.
Statistical Power
21. In statistical testing, what is the alpha error?
False positive/ type 1 error = wanneer er een effect is in de sample maar niet in de popluatie
dus je verwerpt de H0 onrecht. H0 is namelijk waar in de populatie.
22. In statistical testing, what is the beta error?
False negative/ type 2 error = wanneer er geen effect is in de sample maar wel in de
popluatie dus je houdt de H0 onterecht aan. H0 is fout in de populatie.
23. What does the term "effect size" mean?
De grootte van het effect
24. What does the term "statistical power" mean?
Hoe groot de kans dat je een effect vind
25. What does it mean when the statistical power of a study is small or large, respectively?
Small: je vindt geen effect
Large: je vindt een effect
26. In which situations is it important to consider the power of studies?
Before, during and after
27. How is Cohen's effect size value d computed?
(Gem1– gem2) / SD
28. What are the conventional values of d for small, medium, and large effects, respectively?
0.20
0.50
0.80
29. Which factors affect the statistical power of a study?
Alpha error
Effect size
Sample N
30. How can the power of a study be increased? FOUT
Increase N: More participants
Increase effect size
31. Which effect size values are usually used together with t-tests, ANOVAs, and correlations?
T-tests: cohens d
Anova’s: f / eta^2
Correlation: r
32. Why is the correlation a particularly simple and useful effect size value?
Veel gebruikt
33. What are the two main disadvantages of small-sample studies? FOUT
Random fluctuatie
Je leert er niet veel van
General Topics
1. Which types of research can be conducted with observations, correlations, and
experiments,respectively=
Observations: finding phenomen
Correlations: finding relations
Experiments: finding casual
2. What is meant by the precision of a theory?
The accuracy also with multiple measures, the precision with which it can explain something
3. What is meant by the parsimony of a theory?
Should use less assumptions as possible to explain something
4. Why are testability and falsifiability considered important features of a theory?
A theory needs to be disproven otherwise it is not usefull and therefore it needs to be
tested.
5. What is the internal validity of a study?
Does it measure what it is supposed to measure? Does the intervention causes the effect?
6. What is the external validity of a study?
Is it generalizable?
7. What is the construct validity of a study?
Does it measure what it is supposed to measure? Does the test measures the construct?
8. What is the statistical validity of a study?
Is it stastically correct?
9. How can correlations be used and interpreted?
As an relationship between two variables and its strength and direction between these two.
10. How can correlations not be interpreted?
As an causal effect
11. Does correlation imply causality? If yes, why? If not, why not?
No because it means that there is a relationship between the variables and not perse an
causal relationship
12. Does causality imply correlation? If yes, why? If not, why not?
Yes because if there is a causal relationship between the variables, then there is a relation.
13. How does the temporal order of two variables help to establish a causal relation between them?
Helps to determine the causal relationship
If A comes before B then A could be the cause of B, but when B comes before A then A
cannot be the cause of B.
14. What do you have to do to test whether two variables are causally related?
Experiment with manipulation and randomization
15. What are independent, dependent, and control variables of experiments?
IV= manipulated
DV = measured
Control = constant
16. What does it mean if an experimental independent variable is a between-subjects variable?
Each subject gets 1 condition, one measure
17. What does it mean if an experimental independent variable is a within-subjects variable?
Each subject gets every condition, multiple measure.s
, 18. What are advantages and disadvantages of between-subjects and within-subjects experimental
designs?
BS: voordeel is dat je geen order effecten krijgt maar wel veen deelnemers nodig
WS: voordeel: weinig deelnmemers maar je hebt kans op order effecten
19. What is random assignment, and why is it so very important?
Important to assure that possible confounders are ecually distributed between the
conditions
20. What is the difference between a quasi-experiment and a real experiment?
Quasi heft manipulatie maar geen randomisatie.
Statistical Power
21. In statistical testing, what is the alpha error?
False positive/ type 1 error = wanneer er een effect is in de sample maar niet in de popluatie
dus je verwerpt de H0 onrecht. H0 is namelijk waar in de populatie.
22. In statistical testing, what is the beta error?
False negative/ type 2 error = wanneer er geen effect is in de sample maar wel in de
popluatie dus je houdt de H0 onterecht aan. H0 is fout in de populatie.
23. What does the term "effect size" mean?
De grootte van het effect
24. What does the term "statistical power" mean?
Hoe groot de kans dat je een effect vind
25. What does it mean when the statistical power of a study is small or large, respectively?
Small: je vindt geen effect
Large: je vindt een effect
26. In which situations is it important to consider the power of studies?
Before, during and after
27. How is Cohen's effect size value d computed?
(Gem1– gem2) / SD
28. What are the conventional values of d for small, medium, and large effects, respectively?
0.20
0.50
0.80
29. Which factors affect the statistical power of a study?
Alpha error
Effect size
Sample N
30. How can the power of a study be increased? FOUT
Increase N: More participants
Increase effect size
31. Which effect size values are usually used together with t-tests, ANOVAs, and correlations?
T-tests: cohens d
Anova’s: f / eta^2
Correlation: r
32. Why is the correlation a particularly simple and useful effect size value?
Veel gebruikt
33. What are the two main disadvantages of small-sample studies? FOUT
Random fluctuatie
Je leert er niet veel van
