WorksheetsPSY 2020 Final Exam Review
Total questions: 38
Worksheet time: 19mins
Which of the following is NOT a characteristic of a good theory?
support by data
cannot be falsified
as simple as possible (parsimony)
open to modification
What is the role of data analysis in the scientific method?
To collect raw data and create initial hypotheses.
To conduct experiments and observe outcomes.
To test hypotheses and determine the probability of their support.
To prove hypotheses and eliminate the need for further research.
In hypothesis testing, what does the null hypothesis represent?
A prediction that the observed effect is significant and not due to chance.
A claim that there is no difference, and any observed effect is likely due to randomness.
The alternative theory that supports the research hypothesis.
A definitive statement proving the research hypothesis correct.
Which of the following describes the "Theory-Then-Research" approach to scientific investigation?
Collecting data without any prior theory in mind.
Developing a theory, deriving propositions from it, and testing them empirically.
Observing phenomena, analyzing patterns, and creating a theory afterward.
Focusing on practical problem-solving without theoretical guidance.
Translational research is best described as:
Research conducted solely in real-world settings.
The process of translating hypotheses into empirical propositions.
Applying basic research findings to develop treatment or intervention strategies.
The investigation of phenomena without practical implications.
Which statement BEST differentiates qualitative from quantitative research methodologies?
Qualitative research captures subjective experiences, whereas quantitative research involves objective measurements that rely on statistical inference.
Quantitative research emphasizes narrative descriptions, while qualitative research applies structured, numerical methodologies.
Qualitative methods require experimental control, unlike quantitative approaches, which prioritize observation.
Mixed methods research eliminates the distinctions between qualitative and quantitative approaches entirely.
Which of the following MOST accurately describes the primary focus of basic research?
Developing scalable solutions to complex societal problems.
Enhancing the understanding of fundamental principles without immediate practical application.
Creating interdisciplinary models that directly translate into intervention strategies.
Demonstrating the superiority of empirical methods over theoretical constructs.
The closer an R-value is to which of the following, the stronger and more "perfect" the relationship between variables?
0
±0.5
±1
±2
Which criterion for establishing causality is MOST directly challenged by the "third variable problem"?
Temporal precedence
Covariation between variables
Internal validity (non spuriousness)
Construct validity
In confidence intervals, what does a broader range typically indicate, and under what condition is it more commonly observed?
Higher precision, larger sample sizes
Higher precision, smaller sample sizes
Lower precision, larger sample sizes
Lower precision, smaller sample sizes
When making association claims using correlations, which two types of validity are MOST critical to evaluate?
Internal and construct validity
Construct and statistical validity
Statistical and external validity
External and internal validity
Valerie designs a correlational study to explore the relationship between caffeine consumption and GPA among college students. How might the inherent weaknesses of correlational studies manifest in her research?
Directionality is clear, but GPA influences caffeine consumption due to study habits.
There is ambiguity about which variable causes the other, and third variables like stress or sleep may affect the relationship.
The study demonstrates causation but is limited by insufficient statistical validity.
Third variables are irrelevant if the correlation coefficient is statistically significant.
What does the "effect size" in a correlation represent?
The range of the dataset being studied
The strength of the relationship between variables
The confidence interval around the correlation coefficient
The probability that the correlation occurred by chance
Which of the following is an effective strategy to address range restrictions in a dataset?
Decreasing the sample size to focus on extreme scores
Removing outliers from the dataset entirely
Recruiting more participants to increase sample size and variability
Conducting fewer replications to focus on primary results
A study designed to test an association involving more than two measured variables is referred to as:
Univariate design
Bivariate design
Multivariate design
Cross-sectional design
Which type of longitudinal design examines the relationship of a variable with itself over time?
Cross-lag correlation
Auto-correlation
Longitudinal mediation
Temporal sequencing
In a study measuring language development in infants, researchers examine whether earlier vocalizations predict later vocalizations. What type of correlation is being assessed?
Concurrent correlation
Cross-lag correlation
Auto-correlation
Predictive mediation
A researcher determines that physical exercise accounts for part of the relationship between stress and heart health, but not the entire relationship. What is this type of mediation called?
Full mediation
Partial mediation
Direct mediation
Sequential mediation
In a mediation analysis, if the relationship between an independent variable (IV) and a dependent variable (DV) disappears entirely when a mediator is introduced, what is this type of mediation called?
Partial mediation
Moderation analysis
Full mediation
Indirect mediation
Why do experimenters hold “control variables” constant?
To ensure external validity
To generate enough conditions for the study to take place
To account for possible third variables
To ensure validity
Which criteria for causality involves establishing covariance with experiments?
Empirical association
Temporal precedence of the IV
Internal validity
Specify the context/environment in which the experiment occurs
Which criteria for causality involves establishing that the variation in the IV occurs before the variation in the DV?
Empirical association
Temporal precedence of the IV
Internal validity
Specify the context/environment in which the experiment occurs
Which criteria for causality involves establishing sample randomization and third variable/statistical controls?
Empirical association
Temporal precedence of the IV
Internal validity
Specify the context/environment in which the experiment occurs
Which design involves each participant only experiencing 1 level of the IV?
factorial
matched group
between subjects
within subjects
Which is NOT a drawback of between subjects designs?
Requires larger sample sizes
Potential for larger statistical error
Possibility of selection bias
Decreases measurement/test fatigue
What’s a good question to ask if there is a main effect in the plotted variable in a two-way interaction?
Are the averages of the two lines different?
Is one line generally above/below the other?
Are the lines parallel?
Is it a crossover or spreading interaction?
What’s a good question to ask if there is a main effect in the x-axis variable in a two-way interaction?
Are the averages of the two lines different?
Is one line generally above/below the other?
Are the lines parallel?
Is it a crossover or spreading interaction?
Diff between one-way ANOVA and t-test?
One-Way ANOVAs have 2 IV with 2 or more levels; t-tests have 1 IV with no more than 2 levels/groups
One-Way ANOVAs have 1 IV with 2 or more levels; t-tests have 1 IV with no more than 2 levels/groups
One-Way ANOVAs have 1 IV with 1 or more levels; t-tests have 2 IVs with no more than 2 levels/groups
One-Way ANOVAs have 1 IV with 2 or more levels; t-tests have 1 IV with no more than 2 levels/groups
What is an interaction effect?
A result from a factorial design in which levels of one DV have observable differences depending on the level of one IV
A result from a factorial design in which levels of one IV have observable differences depending on the level of the same IV
A result from a factorial design in which levels of one IV have observable differences depending on the level of another IV
A result from a factorial design in which levels of one DV have observable differences depending on the level of one IV
What is a good question to ask to determine if there is a three-way interaction?
Do the two sides show different two-way interactions?
Are the interactions crossover or spreading interactions?
Is there a significant difference in the y-axes of the two-way interactions?
Is there a main effect of IV 3 on IV 1 or 2?
What type of study is most likely to be conducted if researchers are not able to randomly assign participants to the IV conditions, but still want to manipulate a variable?
observational
experimental
correlational
quasi-experimental
What is one significant issue with small-n designs? (ex. Phineas Gage)
small confidence interval
external validity/generalizability
correlational data
moderation analysis
Reviews/studies/meta-analyses are all only based on significant results; however, we have little info about the rates for when those types of studies DON’T work out because _________ are often left in the “file drawer”
null findings
confounds
quasi-experimental studies
small-n designs
Publication bias is the failure to publish the results of a study on the basis of the ________ and/or the strength of the study’s findings.
generalizability
meaning
direction
moderation analysis
What issue can inflate/exaggerate the support for a theory/phenomenon?
file drawer problem
null findings
small-n designs
external validity/generalizability
What is HARKing?
Performing statistical analyses which lead to replicable results
A questionable research practice where researchers create an “after-the-fact” hypothesis about an unexpected research result, making it appear as if they predicted it all along
Using questionable data analysis techniques in order to obtain a p-value of just under 0.05
Utilizing a faulty factorial design
Which is NOT an example of “p-hacking” techniques?
Purposely finding outlier
Performing statistical analyses which lead to replicable result
Adding participants after results are initially analyzed
Purposely disregarding outlier
Why do we need factorial designs?
Causality/relationships are rarely ever dependent on a single IV
To minimize p-hacking
To test the least possible interactions between variables
The extreme prevalence of three-way interactions
