Psychological Research Methods Quiz Questions
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The main effect
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The effect of one factor within a level of another factor
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When each level of an independent variable effects the dependent variable differently
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Differences on the dependent variable across the levels of one
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This quiz assesses key concepts in psychological research methods, focusing on statistical and experimental design validity. It evaluates understanding of main effects, experiment-wise alpha, and internal validity among other topics, crucial for students and professionals in psychology.
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- 2.
Experiment-wise alpha
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The probability that the experimenter made a type 1 error in at least one of the comparisons
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Complex comparisons where more than two means are compared at the same time
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Means comparisons that take into account experiment-wise alpha
Correct Answer
A. The probability that the experimenter made a type 1 error in at least one of the comparisonsExplanation
Experiment-wise alpha refers to the probability that the experimenter made a type 1 error in at least one of the comparisons. This means that when conducting complex comparisons where more than two means are compared at the same time, experiment-wise alpha takes into account the overall probability of making a type 1 error across all comparisons. It provides a more comprehensive measure of the experimenter's risk of incorrectly rejecting a null hypothesis in any of the comparisons.Rate this question:
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- 3.
Pairwise comparisons
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Which means differ significantly from one another
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When one condition mean is compared with another condition mean
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Some factors are between subjects and some are within subjects
Correct Answer
A. When one condition mean is compared with another condition meanExplanation
This answer suggests that pairwise comparisons are used to compare the means of different conditions. It implies that the conditions being compared differ significantly from each other. Additionally, it mentions that there may be factors that are both between subjects and within subjects, indicating the potential complexity of the analysis.Rate this question:
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- 4.
Construct validity
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Conclusions are incorrect because a type I or II error was made
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The measured variables do not relate to the conceptual variables
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The dependent variable was changed by a confounding variable
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The observed effects can be found only under very limited conditions
Correct Answer
A. The measured variables do not relate to the conceptual variablesExplanation
The correct answer is that the measured variables do not relate to the conceptual variables. This means that the variables that were actually measured in the study do not accurately represent or capture the underlying concepts or constructs that the researcher intended to study. As a result, any conclusions drawn from the study based on these measured variables would be incorrect or invalid. This highlights a lack of construct validity in the study design or measurement instruments used.Rate this question:
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- 5.
Statistical conclusion validity
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Conclusions are incorrect because a type I or II error was made
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The measured variables do not relate to the conceptual variables
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The dependent variable was changed by a confounding variable
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The observed effects can be found only under very limited conditions
Correct Answer
A. Conclusions are incorrect because a type I or II error was madeExplanation
The correct answer is "conclusions are incorrect because a type I or II error was made." This means that the conclusions drawn from the study are incorrect because either a type I error (false positive) or a type II error (false negative) was made. These errors occur when the statistical analysis incorrectly rejects or fails to reject the null hypothesis, leading to incorrect conclusions.Rate this question:
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- 6.
Internal validity
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Conclusions are incorrect because a type I or II error was made
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The measured variables do not relate to the conceptual variables
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The dependent variable was changed by a confounding variable
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The observed effects can be found only under very limited conditions
Correct Answer
A. The dependent variable was changed by a confounding variableExplanation
The correct answer is "the dependent variable was changed by a confounding variable." This means that the observed effects in the study were not directly caused by the independent variable, but rather by another variable that was not accounted for or controlled. This confounding variable can introduce bias and lead to incorrect conclusions about the relationship between the independent and dependent variables.Rate this question:
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- 7.
External validity
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Conclusions are incorrect because a type I or II error was made
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The measured variables do not relate to the conceptual variables
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The dependent variable was changed by a confounding variable
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The observed effects can be found only under very limited conditions
Correct Answer
A. The observed effects can be found only under very limited conditionsExplanation
The correct answer suggests that the conclusions drawn from the study may only be applicable under very specific and limited conditions. This means that the effects observed in the study may not be generalizable to other populations or settings. In other words, the findings may not hold true in different contexts or with different samples.Rate this question:
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- 8.
Extraneous variables
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Random error may increase the likelihood of a type II error may reduce power
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Systematic error, which provides an alternative explanation for the results
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The extent to which the manipulation involves the participants in the research
Correct Answer
A. Random error may increase the likelihood of a type II error may reduce powerExplanation
Random error refers to the unpredictable and uncontrollable fluctuations in data that can occur during the research process. These errors can occur due to various factors such as measurement errors, human error, or equipment malfunction. Random errors can lead to inaccurate or inconsistent results, which can increase the likelihood of making a type II error. A type II error occurs when the null hypothesis is incorrectly accepted, meaning that a true effect or relationship is not detected. Additionally, random errors can also reduce the statistical power of a study, making it more difficult to detect true effects or relationships.Rate this question:
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- 9.
Experimenter bias
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When expectations effect the dependent variable
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When participants guess the research hypothesis, to eliminate this cover stories, unrelated experiments, and nonreactive measures can be used
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The experimenter may treat subjects differently because they know what condition they’re in, to avoid this naive or blind experimenters can be used
Correct Answer
A. The experimenter may treat subjects differently because they know what condition they’re in, to avoid this naive or blind experimenters can be usedExplanation
Experimenter bias refers to the potential influence that the experimenter's expectations and knowledge about the study can have on the way they treat subjects. This bias can inadvertently affect the dependent variable, leading to skewed results. To mitigate this bias, researchers can employ naive or blind experimenters who are unaware of the conditions or hypotheses of the study. This helps ensure that the treatment of subjects remains consistent across all conditions, reducing the likelihood of experimenter bias influencing the results.Rate this question:
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- 10.
External validity
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The extent to which results can be generalized outside the experimental conditions
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The extent to which the research is conducted in situations that are similar to everyday life
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When a study creates the hoped-for changes
Correct Answer
A. The extent to which results can be generalized outside the experimental conditionsExplanation
The correct answer is "the extent to which results can be generalized outside the experimental conditions." This refers to how well the findings of a study can be applied to real-world situations beyond the specific conditions of the experiment. It is important for research to have external validity in order for the results to have practical implications and be applicable to a wider population or context.Rate this question:
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- 11.
Exact replication
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Repeating the experiment exactly how it was previously done
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Comparing a new population to the original population
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Testing the same conceptual variable, but with a different operational definition
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Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
A. Repeating the experiment exactly how it was previously doneExplanation
The correct answer is "repeating the experiment exactly how it was previously done." This means conducting the experiment in the same way, using the same procedures, materials, and conditions as the original experiment. By doing so, researchers can determine if the same results are obtained, which helps to establish the reliability and validity of the findings.Rate this question:
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- 12.
Conceptual replication
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Repeating the experiment exactly how it was previously done
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Comparing a new population to the original population
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Testing the same conceptual variable, but with a different operational definition
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Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
A. Testing the same conceptual variable, but with a different operational definitionExplanation
Conceptual replication refers to conducting a study that tests the same theoretical concept as a previous study, but with a different operational definition. This means that while the underlying idea being investigated remains the same, the specific way in which it is measured or manipulated may vary. By using a different operational definition, researchers can assess whether the findings of the original study hold true across different ways of operationalizing the concept. This helps to strengthen the validity and generalizability of the findings, as it demonstrates that the results are not dependent on a specific operationalization.Rate this question:
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- 13.
Constructive replication
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Repeating the experiment exactly how it was previously done
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Comparing a new population to the original population
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Testing the same conceptual variable, but with a different operational definition
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Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
A. Adding new conditions to an experiment to rule out alternative explanationsExplanation
The correct answer is adding new conditions to an experiment to rule out alternative explanations. This is because by adding new conditions, researchers can control for potential confounding variables and ensure that any observed effects are truly due to the manipulated variable. This helps to strengthen the internal validity of the study and provides more confidence in the conclusions drawn from the results.Rate this question:
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- 14.
Participant replication
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Repeating the experiment exactly how it was previously done
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Comparing a new population to the original population
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Testing the same conceptual variable, but with a different operational definition
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Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
A. Comparing a new population to the original populationExplanation
The correct answer is comparing a new population to the original population. This involves conducting the experiment again with a different group of participants, but keeping all other variables and conditions the same. By comparing the results of the new population to the original population, researchers can determine if the findings are consistent and generalizeable to different groups. This helps to establish the reliability and validity of the experiment.Rate this question:
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- 15.
Quasi-experiments lack random assignment
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Cannot be sure that the program and the control group are equivalent
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Unable to control for all threats to internal validity
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All of the above
Correct Answer
A. All of the aboveExplanation
The given correct answer is "all of the above" because quasi-experiments lack random assignment, which means that the program and control group are not equivalent. Additionally, quasi-experiments are unable to control for all threats to internal validity, which further undermines the certainty of the results. Therefore, all of these statements are true and contribute to the limitations of quasi-experiments.Rate this question:
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- 16.
Attrition (mortality) threats:
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Changes in the research participants over time
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People who stay with the program may be different than those who drop out
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Changes in the social climate over time
Correct Answer
A. People who stay with the program may be different than those who drop outExplanation
Attrition (mortality) threats refer to the changes in the research participants over time, where people who drop out of the program may be different from those who choose to stay. This can introduce bias in the results as the characteristics and behaviors of those who drop out may differ from those who remain in the study. This can impact the generalizability and validity of the findings, as the sample may no longer be representative of the target population.Rate this question:
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- 17.
Time-series designs
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Measuring changes in a single person
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Grouping based on preexisting characteristics (e.g sex)
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The dependent variable is assessed regularly both before and after the intervention
Correct Answer
A. The dependent variable is assessed regularly both before and after the interventionExplanation
The given answer suggests that in time-series designs, the dependent variable is measured at regular intervals before and after the intervention. This implies that the researcher collects data on the variable of interest multiple times over a period of time to observe any changes that occur due to the intervention. This design allows for the examination of the effects of the intervention over time and helps to establish a cause-and-effect relationship between the intervention and the dependent variable.Rate this question:
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Current Version
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Mar 22, 2023Quiz Edited by
ProProfs Editorial Team -
May 09, 2018Quiz Created by
Saraghananem
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