Chapter 1: Research Methods In Psychology (Grivas)

In an experiment, the group that receives the treatment is called the experimental group because they are the ones who are exposed to the independent variable being tested. On the other hand, the group that does not receive the treatment is called the control group. They serve as a baseline for comparison and help to determine the effectiveness of the treatment by providing a point of reference.

The independent variable in this experiment is the use of the learning technique, as it is the variable that is manipulated by the researchers. The dependent variable is the number of Greek words correctly recalled, as it is the variable that is measured and expected to be influenced by the independent variable.

The correct answer is describing the independent and dependent variables in terms of how they will be observed, manipulated and measured. This involves providing a detailed explanation of how the variables will be observed, manipulated, and measured in the experiment. By doing so, researchers can ensure that the variables are operationalized effectively and that the experiment is conducted in a controlled and systematic manner. This step is crucial in experimental research as it helps to establish the validity and reliability of the study.

Ethical guidelines in psychological research are put in place to prioritize the rights and wellbeing of participants. These guidelines ensure that participants are not subjected to any harm or distress during the research process. It also ensures that their privacy and confidentiality are protected. By following these ethical guidelines, researchers can conduct their studies in an ethical and responsible manner, minimizing any potential negative impact on the participants.

In an experiment, the independent variable is manipulated. This means that the researcher deliberately changes or controls the independent variable to observe its effect on the dependent variable. The dependent variable, on the other hand, is the variable that is measured or observed to determine the outcome of the experiment. By manipulating the independent variable, researchers can study the cause-and-effect relationship between variables and draw conclusions about the effects of the independent variable on the dependent variable.

This answer is correct because strict control of extraneous and potential confounding variables ensures that any observed effects can be attributed solely to the independent variable. By eliminating the influence of other variables, the researcher can confidently conclude that any changes in the dependent variable are directly caused by the independent variable. This increases the internal validity of the experiment and strengthens the causal relationship between the variables being studied.

Diary records kept by a person with a spider phobia on how they think and feel whenever they see a spider is an example of a self-report because it involves the individual reporting their own thoughts and feelings. This type of self-report allows the person to provide subjective information about their experiences and perceptions, which can be valuable in understanding their psychological state.

The researcher identified and minimized potential extraneous variables to ensure that there would be no confounding variables. Confounding variables are variables that are not the independent variable but can affect the dependent variable, leading to inaccurate or misleading results. By eliminating or minimizing the influence of these variables, the researcher can have more confidence in the relationship between the independent and dependent variables and draw accurate conclusions from the experiment.

An interview usually involves oral responses to orally presented questions, while a questionnaire usually involves written responses to written questions presented by the researcher.

Random allocation and random sampling differ in their purpose and procedure. Random allocation is used to place participants in different groups or conditions in an experiment, ensuring that each participant has an equal chance of being assigned to any group. This helps to minimize bias and ensure that the groups are comparable. On the other hand, random sampling is used to select participants from a larger population to be included in a study. It ensures that each member of the population has an equal chance of being selected, increasing the generalizability of the findings.

In a repeated-measures experimental design, each participant is exposed to all conditions of the experiment. This means that every participant experiences every level or variation of the independent variable. This design allows researchers to compare the effects of different conditions within the same participants, reducing individual differences and increasing the statistical power of the study. By exposing participants to all conditions, researchers can determine the impact of the independent variable on the dependent variable more accurately.

In this experiment, the researcher is giving vitamin C to one group and a placebo to another group to measure the effect on the common cold. The frequency of colds is the variable that is being measured and observed in response to the independent variable, which is the administration of vitamin C or placebo. Therefore, the frequency of colds is the dependent variable in this experiment.

The double-blind procedure is the best technique for ensuring control over demand characteristics and experimenter effects. This procedure involves both the participants and the experimenters being unaware of which group is receiving the treatment and which group is receiving the placebo. By keeping both parties blind to this information, it minimizes the potential for bias and ensures that any observed effects are truly due to the treatment being tested rather than participant or experimenter expectations.

The correct answer is "applying the findings obtained from a sample to the population." This is because generalization involves taking the results obtained from a sample and applying them to the larger population from which the sample was drawn. By doing so, researchers can make inferences and draw conclusions about the entire population based on the findings from the sample. This allows for a broader understanding of the phenomenon being studied and increases the external validity of the research.

Preventing a participant from leaving an experiment midway through the experiment would be considered unethical because it violates the principle of voluntary participation. Participants should have the right to withdraw from a study at any time without facing any negative consequences. It is important to respect the autonomy and well-being of participants, and coercing or preventing them from leaving goes against ethical guidelines for research.

Counterbalancing is the correct answer because it refers to the intentional arrangement of the order in which conditions of a repeated-measures experiment are experienced. This is done to control order effects that may occur. Counterbalancing helps to ensure that any potential biases or confounding variables associated with the order of conditions are evenly distributed across participants, thus increasing the internal validity of the study. Biased participant selection, unethical behavior, and biased participant allocation do not accurately describe the procedure of intentionally arranging the order of conditions in a repeated-measures experiment.

Selecting students whose VCE candidate number ends with an even number would provide a random sample of VCE students in a school. This method ensures that all students have an equal chance of being selected, as the candidate number is unrelated to any other factors such as their academic performance or personal characteristics. This approach eliminates bias and allows for a representative sample of VCE students to be obtained.

The matched-participants experimental design involves allocating each member of a pair of participants, who are very similar in a characteristic likely to influence the dependent variable, to different groups or conditions. This design is used to control for individual differences and ensure that any differences observed between the groups are due to the independent variable and not other factors. By matching participants based on a relevant characteristic, the design aims to eliminate the confounding effects of that characteristic on the dependent variable.

Counterbalancing refers to a method used in experimental design to control for potential confounding variables. By systematically varying the order in which conditions are presented to participants, any effects of the order are balanced out across all experimental conditions. This helps ensure that any observed differences in the dependent variable can be attributed to the independent variable rather than other extraneous factors.

The correct answer is stratified-random sampling. This is because the researcher is intentionally selecting participants from different groups within the target population (stratified sampling) and doing so randomly (random sampling). By ensuring that the characteristics of sex and religious beliefs are proportionally represented in the sample, the researcher is reducing potential biases and increasing the generalizability of the results.

The p value represents the level of significance in hypothesis testing. A smaller p value indicates stronger evidence against the null hypothesis. In this case, p ≤ 0.001 is the strictest because it requires the strongest evidence to reject the null hypothesis. It means that the observed data is extremely unlikely to occur by chance alone, leading to a high level of confidence in the alternative hypothesis.

The correct answer is independent-groups. In this experimental design, participants are divided into two groups: one group is exposed to the independent variable (experimental group) and the other group is not exposed to the independent variable (control group). This design allows researchers to compare the effects of the independent variable by comparing the outcomes of the two groups.

The statistical test result with a p-value less than 0.05 indicates that the difference in scores between the two groups is unlikely to occur by chance. This means that there is a significant difference between the number of words correctly recalled by the two groups. The answer suggests that a difference equal to or greater than the difference found in this experiment is likely to occur by chance less than 5% of the time the experiment is replicated, further supporting the conclusion that the difference is not due to chance.

A statistically significant difference in the mean scores of groups in an experiment suggests that the role of chance is at an acceptable level. This means that the difference in scores is unlikely to have occurred purely by chance, and there is a high level of confidence that the results are due to the variables being studied rather than random variation.

In a repeated-measures design, each participant is exposed to all levels of the independent variable. Since the same participant is used for all conditions, the minimum number of participants required is one. This is because the focus is on within-subject differences rather than between-subject differences. The other options are not relevant to determining the minimum number of participants needed for this type of design.