- In a clinical trial, a 'double-blind' procedure is implemented to minimize the influence of:
Answer: expectancy effects on the part of both the participants and the researchers.
A double-blind procedure means that neither the participants nor the researchers interacting with them know who is in the experimental group and who is in the control group. This is done to control for two types of expectancy effects: 1) participant expectations (placebo effects) and 2) researcher expectations, which could cause them to subtly treat participants differently or interpret data in a biased way. 'A' is controlled by random assignment. 'C' is a threat of attrition. 'D' is controlled by proper sampling methods.
- Why is the district's causal conclusion not well-supported by this research design?
Answer: Pre-existing systemic differences between high-poverty and low-poverty schools were not controlled for.
This is a quasi-experimental design because the groups (high- vs. low-poverty schools) were not created through random assignment. Therefore, there could be many systematic differences between them other than the curriculum (e.g., teacher resources, parental involvement, student health) that could explain the difference in outcomes. This is a major confound. 'A' is incorrect; the standard curriculum schools serve as a comparison group. 'B' is a potential measurement issue but not the core design flaw. 'C' is a true but imprecise statement; 'D' provides the specific reason why the study is only correlational and cannot support a causal claim.
- The use of identical-tasting decaffeinated coffee for Group B is a critical part of this design because it serves as a:
Answer: placebo control to account for the effects of participant expectations.
The goal is to isolate the chemical effects of caffeine. By giving the control group a beverage that is identical in every way except for the active ingredient (caffeine), the researcher controls for the psychological effects of simply being in an experiment and consuming what one believes is coffee. This is a placebo control. Any difference between the groups can then be more confidently attributed to the caffeine itself, rather than to participant expectations. 'A' refers to checking if the IV manipulation worked. 'C' is too general. 'D' is a participant characteristic that is controlled by random assignment.
- What is the dependent variable in this experiment?
Answer: The participant's self-rated confidence score.
The dependent variable (DV) is the outcome that the researcher measures to see if it is affected by the independent variables. In this case, the researcher is measuring the participants' confidence ratings. 'A' and 'B' are the two independent variables that are being manipulated by the researcher. 'D' is a potential result or finding of the study (i.e., whether the effect of one IV depends on the level of the other IV), but it is not the variable being directly measured from each participant.
- Based on the experimental design and the graph, what are the independent and dependent variables? Use the graph below to answer the question.
Answer: IV is the amount of sleep; DV is the average reaction time.
The independent variable (IV) is what the researcher manipulates, which is the amount of sleep (8 hours vs. 4 hours), shown on the x-axis. The dependent variable (DV) is what the researcher measures as an outcome, which is the average reaction time in milliseconds, shown on the y-axis. 'B' incorrectly reverses the IV and DV. 'C' and 'D' misidentify the variables based on information that is either constant for all participants (the location) or not part of the described experiment (type of task).
- A cognitive psychologist wants to test if a new mnemonic technique improves memory for lists of words. She randomly assigns 100 undergraduates to either a group that learns the new technique or a group that uses their own typical study methods. The primary purpose of randomly assigning participants is to:
Answer: increase the likelihood that pre-existing differences in memory ability are balanced between the two groups.
Random assignment is a core feature of experimental design used to increase internal validity. Its purpose is to create groups that are approximately equivalent at the start of the study by distributing individual differences (like baseline memory ability, motivation, intelligence) between the groups by chance. 'A' describes the purpose of random sampling, which affects external validity (generalizability). 'C' refers to situational variables that must be controlled through standardization of procedures. 'D' relates to controlling for expectancy effects, which is typically addressed with blinding and placebo controls.
- The difference in the testing environment (library vs. student center) represents a:
Answer: confounding variable that provides an alternative explanation for the results.
When evaluating experimental design, you need to identify factors that could systematically bias your results. This question tests your ability to recognize threats to internal validity—the degree to which you can confidently attribute observed effects to your independent variable rather than other factors.
The correct answer is A because the testing environment creates a confounding variable. A confound is an extraneous factor that varies systematically with your independent variable and could plausibly explain your results. Here, the study technique (independent variable) is completely entangled with testing location and time of day. If the experimental group performs better, you can't determine whether it's due to the new study technique, the quiet library environment, or testing in the morning when students might be more alert.
Option B is incorrect because this isn't random error—it's systematic bias. Random error would occur if participants were randomly assigned to different environments, creating variability but not consistent bias in one direction.
Option C misidentifies the problem. The issue isn't with random assignment itself, but with the systematic difference in testing conditions between groups after assignment.
Option D is wrong because testing environment isn't part of how the study technique is defined or implemented—it's an uncontrolled external factor.
Remember this key principle: confounding variables are the "third variable problem" in experiments. Always scan for factors that differ systematically between groups and could reasonably influence your dependent variable. Strong experimental design controls these variables to isolate the true effect of your manipulation.
- Despite the strong experimental design, which of the following could still threaten the internal validity of the causal claim?
Answer: Differential attrition, if participants with severe side effects disproportionately dropped out of the drug group.
Internal validity is the degree to which a study supports a causal conclusion. Even with random assignment, a threat can emerge if participants drop out of the study (attrition) at different rates in the two groups. For example, if those for whom the drug isn't working or who have bad side effects drop out, the final drug group will consist only of those who responded well, artificially inflating the drug's apparent effectiveness. 'A' concerns external validity (generalizability). 'B' and 'C' are problems (third variable, directionality) that random assignment and manipulation of the IV are specifically designed to solve.
- This outcome indicates that the causal effect of the tutoring method on student learning:
Answer: is dependent on the students' level of prior math achievement.
When you encounter experimental design questions in psychology, focus on identifying the relationship between variables and whether effects depend on other factors. This study uses a factorial design that can reveal interactions between variables.
The key finding here is that the tutoring method's effectiveness varies based on students' prior achievement level - it helps low achievers but doesn't benefit high achievers. This describes an interaction effect, where the impact of one variable (tutoring method) depends on the level of another variable (prior achievement). The correct answer is A because the causal effect of tutoring is indeed dependent on students' prior math achievement.
Let's examine why the other options are incorrect. Option B suggests the main effect of prior achievement is more important than the tutoring effect, but the question asks specifically about the nature of the tutoring method's causal effect, not which variable is more influential. Option C claims confounding, but since students were randomly assigned to conditions, prior achievement isn't confounding the results - it's a measured factor that moderates the treatment effect. Option D focuses on the overall positive outcome, but this misses the crucial point about how the effect varies by subgroup.
When studying experimental design, remember that interaction effects occur when the impact of one independent variable depends on the level of another independent variable. Look for phrases like "effective for some but not others" or "depends on" as clues that you're dealing with interactions rather than simple main effects.
- Based on this specific causal claim, the study most likely employed which research method?
Answer: An experiment where participants were randomly assigned to an exercise condition or a no-exercise control condition.
The word "causes" implies a causal relationship. To establish causation, a researcher must conduct a true experiment, which involves manipulating the independent variable (exercise) and using random assignment to control for pre-existing differences. Correlational, longitudinal, and case study methods can identify relationships and generate hypotheses, but they cannot, on their own, establish cause and effect due to the third-variable problem and/or the directionality problem.
- In this study, which of the following is the independent variable?
Answer: The specific 15-minute daily activity participants were assigned.
The independent variable (IV) is the factor that the researcher manipulates to observe its effect. In this experiment, the researcher is systematically varying the type of daily activity across three levels: mindfulness app, quiet sitting, and no instructions. Therefore, the assigned activity is the IV. 'A' is the dependent variable (the outcome being measured). 'B' is an extraneous variable being tracked. 'D' is an incomplete description of the IV, as it ignores the second, active control group (quiet sitting) and reduces the three-level variable to a two-level comparison.
- A primary methodological challenge specific to this within-subjects design is:
Answer: the potential for order effects, such as practice or fatigue, to influence the ratings in the second condition.
This is a within-subjects (or repeated measures) design because the same participants are in both conditions. A key disadvantage of this design is the potential for order effects: the experience of being in the first condition can influence performance in the second. For example, participants might be bored by the second session (fatigue effect) or get better at the rating task (practice effect). 'A' is incorrect because a major strength of this design is that it eliminates concerns about initial group equivalence on individual differences. 'C' and 'D' are general research challenges not specific to this design type.
- A researcher manipulates a variable of interest and includes a comparison group, but does not use random assignment to place participants in the groups. Which statement most accurately describes this study?
Answer: It is a quasi-experiment whose ability to support a causal claim is weakened.
When you encounter questions about research design, focus on the three key elements that distinguish experimental approaches: manipulation of variables, comparison groups, and random assignment. Each element affects what conclusions you can draw from the study.
This study has two of the three experimental elements—variable manipulation and a comparison group—but lacks random assignment. This makes it a quasi-experiment. Random assignment is crucial because it helps ensure that groups are equivalent at the start, reducing the chance that pre-existing differences between participants (rather than your manipulation) explain any observed effects. Without it, your ability to make strong causal claims is compromised, though not eliminated entirely.
Choice A correctly identifies this as a quasi-experiment with weakened causal inference. The study can still provide valuable evidence, but you must be more cautious about claiming causation.
Choice B is wrong because true experiments require all three elements, including random assignment. Variable manipulation alone isn't sufficient.
Choice C incorrectly labels this as correlational. Correlational studies don't involve manipulation—they just measure existing relationships between variables. Since this study manipulates a variable, it's experimental in nature, just not a true experiment.
Choice D reverses the validity issue. This design actually has potentially low internal validity (ability to infer causation) due to the lack of random assignment, though external validity could vary depending on other design features.
Remember: quasi-experiments fall between correlational and true experimental designs. They're stronger than correlational studies but weaker than true experiments for establishing causation.
- Which statement best explains why a well-designed experiment can justify a causal claim, whereas a correlational study cannot?
Answer: Experiments involve the direct manipulation of one variable and random assignment to control for others, isolating the variable's effect.
The logical foundation of an experiment's ability to demonstrate cause and effect rests on two key features: 1) manipulation of the independent variable, which establishes temporal precedence, and 2) random assignment, which controls for pre-existing differences between groups (addressing the third-variable problem). Together, these elements allow researchers to isolate the effect of the IV on the DV. 'A' is incorrect, as both designs can use either type of data. 'B' is a common misconception; statistics can show the strength of a relationship, but the research design determines whether a causal inference is warranted. 'D' is often false; many experiments use convenience samples, and sample size relates more to statistical power and generalizability than to the logic of causation.
- A researcher wants to conduct an experiment to test the hypothesis that 'stress impairs memory.' Which of the following designs provides the best operationalization of the independent and dependent variables for this purpose?
Answer: Randomly assigning participants to either submerge their hand in ice water (a stressor) or lukewarm water, and then having them recall a list of words.
A good experiment must manipulate the IV (stress) and measure the DV (memory). 'D' does this effectively: it manipulates stress using a standardized procedure (cold pressor test) and measures memory with a recall task. 'A' is a correlational design, not an experiment. 'B' operationalizes stress but fails to measure the correct dependent variable (memory); it measures arousal instead. 'C' is a quasi-experimental design because it uses pre-existing groups rather than manipulating stress directly, so other factors associated with anxiety disorders could be confounds.
- In this experiment, the independent variable has been operationalized as:
Answer: the type of formula (omega-3 enriched vs. standard) provided to the infants.
Operationalization refers to the specific, concrete way a conceptual variable is manipulated or measured. The conceptual independent variable is 'omega-3 consumption,' but the way the researcher actually manipulated it (its operational definition) was by providing one of two types of formula. 'A' is the operationalized dependent variable. 'C' is the conceptual dependent variable. 'D' is close but less precise than 'B'; the researcher is not measuring the exact amount consumed, but rather assigning groups based on the type of formula they are given.
- The company's conclusion is most weakened because the control group:
Answer: fails to control for placebo effects or the effects of engaging in any structured activity.
The improvement in the experimental group could be due to the game itself, or it could be due to other factors like the expectation of improving (placebo effect), the novelty of the task, or simply the effect of spending 30 minutes a day doing a structured, engaging computer task. A 'no-treatment' control group like this one doesn't account for these alternative explanations. A better design would use an 'active control,' where the control group plays a different, non-brain-training game for the same amount of time. 'A' is a good practice but less critical than the control issue. 'B' is part of the problem, but 'C' is a more comprehensive explanation of the design flaw. 'D' is contradicted by the stem.
- The most significant flaw that prevents a valid causal conclusion in this study is the:
Answer: confounding of the independent variable (location) with the weather conditions.
A confounding variable is an extraneous variable that varies systematically along with the independent variable, providing an alternative explanation for the results. In this case, location (park vs. room) is perfectly confounded with weather (sunny vs. rainy). It is impossible to know if the better mood was caused by being in nature or by the pleasant sunny weather. 'A' is not a flaw; self-report is a standard way to measure mood. 'B' is a weakness, but less critical than the confound. 'D' is incorrect as the windowless room group serves as a comparison/control condition, albeit a flawed one.
- In this experiment, what is the role of the IQ test?
Answer: It is a measured variable used to check the initial equivalence of the randomly assigned groups.
The IQ test is not being manipulated (so it's not an IV) and it's not the outcome of interest (so it's not the DV). Instead, it is measured to verify that random assignment was successful in creating groups that are, on average, equivalent in terms of general cognitive ability. If one group happened to have a significantly higher average IQ by chance, it could compromise the study's internal validity. Measuring it allows the researchers to confirm this is not the case or statistically control for it if necessary.
