Research Methods In Psychology Quiz

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.

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.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.