Research Methods In Psychology Quiz
Research methods
- 1.
The main effect
- A.
The effect of one factor within a level of another factor
- B.
When each level of an independent variable effects the dependent variable differently
- C.
Differences on the dependent variable across the levels of one
Correct Answer
C. Differences on the dependent variable across the levels of oneExplanation
The correct answer suggests that the main effect refers to the differences on the dependent variable across the levels of one factor. In other words, it is the impact or influence that a single independent variable has on the dependent variable, without considering any other factors. The main effect allows researchers to understand how changes in one factor affect the outcome variable, providing valuable insights into the relationship between variables.Rate this question:
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- 2.
Experiment-wise alpha
- A.
The probability that the experimenter made a type 1 error in at least one of the comparisons
- B.
Complex comparisons where more than two means are compared at the same time
- C.
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 has made a type 1 error in at least one of the comparisons. It is used in complex comparisons where more than two means are compared simultaneously and takes into account the overall probability of making a type 1 error across all comparisons. By considering experiment-wise alpha, researchers can assess the likelihood of false positive results in their study, which helps to control the overall false positive rate and maintain the integrity of the findings.Rate this question:
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- 3.
Pairwise comparisons
- A.
Which means differ significantly from one another
- B.
When one condition mean is compared with another condition mean
- C.
Some factors are between subjects and some are within subjects
Correct Answer
B. 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 also indicates that these conditions can differ significantly from each other. Additionally, the answer mentions that there may be factors that are between subjects (i.e., different individuals) and factors that are within subjects (i.e., within the same individual).Rate this question:
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- 4.
Construct validity
- A.
Conclusions are incorrect because a type I or II error was made
- B.
The measured variables do not relate to the conceptual variables
- C.
The dependent variable was changed by a confounding variable
- D.
The observed effects can be found only under very limited conditions
Correct Answer
B. The measured variables do not relate to the conceptual variablesExplanation
The correct answer is "the measured variables do not relate to the conceptual variables." This means that the variables being measured in the study do not accurately represent or correspond to the underlying concepts or constructs that the researcher is trying to study. As a result, any conclusions drawn from the study based on these measured variables would be invalid and incorrect.Rate this question:
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- 5.
Statistical conclusion validity
- A.
Conclusions are incorrect because a type I or II error was made
- B.
The measured variables do not relate to the conceptual variables
- C.
The dependent variable was changed by a confounding variable
- D.
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 that the conclusions are incorrect because a type I or II error was made. This means that either a false positive (type I error) or a false negative (type II error) occurred in the statistical analysis, leading to incorrect conclusions. Type I errors happen when a true null hypothesis is rejected, while type II errors occur when a false null hypothesis is not rejected. Both types of errors can lead to incorrect conclusions and affect the validity of the statistical analysis.Rate this question:
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- 6.
Internal validity
- A.
Conclusions are incorrect because a type I or II error was made
- B.
The measured variables do not relate to the conceptual variables
- C.
The dependent variable was changed by a confounding variable
- D.
The observed effects can be found only under very limited conditions
Correct Answer
C. 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 actually caused by the independent variable being studied, but rather by another variable that was not accounted for. This confounding variable could have influenced the dependent variable and led to incorrect conclusions being drawn.Rate this question:
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- 7.
External validity
- A.
Conclusions are incorrect because a type I or II error was made
- B.
The measured variables do not relate to the conceptual variables
- C.
The dependent variable was changed by a confounding variable
- D.
The observed effects can be found only under very limited conditions
Correct Answer
D. The observed effects can be found only under very limited conditionsExplanation
The correct answer is "the observed effects can be found only under very limited conditions." This means that the conclusions drawn from the study may only be applicable in specific situations or settings. The results may not be generalizable to a larger population or different contexts.Rate this question:
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- 8.
Extraneous variables
- A.
Random error may increase the likelihood of a type II error may reduce power
- B.
Systematic error, which provides an alternative explanation for the results
- C.
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 variability or fluctuations in data that are caused by chance factors. It is unrelated to the variables being studied and can occur in any research study. Random error can affect the accuracy and precision of measurements, leading to inconsistencies in the data. In the context of the given options, random error may increase the likelihood of a type II error, which is the failure to reject a false null hypothesis. This means that random error can make it more likely for researchers to incorrectly conclude that there is no effect or relationship when there actually is. Additionally, random error may reduce the statistical power of a study, which is the ability to detect an effect if it truly exists.Rate this question:
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- 9.
Experimenter bias
- A.
When expectations effect the dependent variable
- B.
When participants guess the research hypothesis, to eliminate this cover stories, unrelated experiments, and nonreactive measures can be used
- C.
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
C. 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 situation where the experimenter's knowledge or expectations about the experimental conditions influence their treatment of the subjects. This can lead to biased results as the experimenter's behavior may inadvertently affect the dependent variable. To mitigate this bias, researchers can use naive or blind experimenters who are unaware of the experimental conditions, ensuring that they treat all subjects equally and minimizing the potential for bias.Rate this question:
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- 10.
External validity
- A.
The extent to which results can be generalized outside the experimental conditions
- B.
The extent to which the research is conducted in situations that are similar to everyday life
- C.
When a study creates the hoped-for changes
Correct Answer
A. The extent to which results can be generalized outside the experimental conditionsExplanation
External validity refers to the degree to which the findings of a study can be applied or generalized to real-world settings and populations beyond the specific conditions of the experiment. It is concerned with whether the results obtained in a controlled laboratory setting can be applied to a wider range of situations and individuals. This concept helps researchers determine the extent to which their findings can be considered applicable and relevant in practical settings.Rate this question:
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- 11.
Exact replication
- A.
Repeating the experiment exactly how it was previously done
- B.
Comparing a new population to the original population
- C.
Testing the same conceptual variable, but with a different operational definition
- D.
Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
A. Repeating the experiment exactly how it was previously doneExplanation
The term "exact replication" refers to the process of repeating an experiment in the exact same manner as it was previously conducted. This means following the same procedures, using the same materials, and replicating all the conditions and variables involved. By doing so, researchers aim to determine if the same results can be obtained, which helps validate the findings and assess the reliability of the original experiment.Rate this question:
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- 12.
Conceptual replication
- A.
Repeating the experiment exactly how it was previously done
- B.
Comparing a new population to the original population
- C.
Testing the same conceptual variable, but with a different operational definition
- D.
Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
C. Testing the same conceptual variable, but with a different operational definitionExplanation
Conceptual replication refers to the process of testing the same conceptual variable, but with a different operational definition. This means that researchers aim to replicate a study by examining the same underlying concept or idea, but they use a different way of measuring or operationalizing that concept. By doing so, they can verify the robustness and generalizability of the original findings, as well as gain a deeper understanding of the phenomenon under investigation.Rate this question:
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- 13.
Constructive replication
- A.
Repeating the experiment exactly how it was previously done
- B.
Comparing a new population to the original population
- C.
Testing the same conceptual variable, but with a different operational definition
- D.
Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
D. 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 involves introducing additional variables or conditions to the experiment in order to eliminate any potential confounding factors or alternative explanations for the observed results. By systematically varying the conditions and controlling for potential confounds, researchers can strengthen the validity and reliability of their findings. This process is essential for ensuring that the observed effects are indeed caused by the manipulated variables and not by any other factors.Rate this question:
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- 14.
Participant replication
- A.
Repeating the experiment exactly how it was previously done
- B.
Comparing a new population to the original population
- C.
Testing the same conceptual variable, but with a different operational definition
- D.
Adding new conditions to an experiment to rule out alternative explanations
Correct Answer
B. Comparing a new population to the original populationExplanation
The correct answer is comparing a new population to the original population. This involves studying a different group of individuals and comparing their results to those of the original group. By doing so, researchers can determine if the findings from the original study are consistent across different populations, increasing the generalizability and reliability of the results.Rate this question:
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- 15.
Quasi-experiments lack random assignment
- A.
Cannot be sure that the program and the control group are equivalent
- B.
Unable to control for all threats to internal validity
- C.
All of the above
Correct Answer
C. All of the aboveExplanation
The correct answer is "all of the above" because quasi-experiments lack random assignment, which means that the program and control group may not be equivalent. Additionally, without random assignment, it is difficult to control for all threats to internal validity, such as selection bias or confounding variables. Therefore, all of these statements are true and explain why quasi-experiments cannot provide the same level of certainty as true experiments with random assignment.Rate this question:
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- 16.
Attrition (mortality) threats:
- A.
Changes in the research participants over time
- B.
People who stay with the program may be different than those who drop out
- C.
Changes in the social climate over time
Correct Answer
B. People who stay with the program may be different than those who drop outExplanation
Attrition (mortality) threats refer to the changes in research participants over time, specifically when people who drop out of a program are different from those who stay. This can introduce bias into the study results, as the characteristics and experiences of those who remain in the program may not be representative of the entire population. It is important to consider attrition rates and potential differences between dropouts and participants who complete the program to ensure the validity and generalizability of the findings.Rate this question:
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- 17.
Time-series designs
- A.
Measuring changes in a single person
- B.
Grouping based on preexisting characteristics (e.g sex)
- C.
The dependent variable is assessed regularly both before and after the intervention
Correct Answer
C. The dependent variable is assessed regularly both before and after the interventionExplanation
This answer suggests that in time-series designs, the dependent variable is measured at regular intervals both before and after the intervention. This allows for the observation of any changes in the variable over time and the assessment of the intervention's impact.Rate this question:
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Current Version
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Jul 20, 2023Quiz Edited by
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May 28, 2015Quiz Created by
Noyon