Research Methods In Psychology Quiz

Random sampling refers to the process of selecting individuals from a population in a way that gives everyone an equal chance of being chosen. This method is commonly used in research studies to ensure that the sample is representative of the larger population. By randomly selecting participants, researchers can minimize bias and increase the generalizability of their findings. Therefore, the statement that random sampling refers to when all people in a target population have an equal chance of being selected for an experiment is true.

The given statement is true because an experiment is indeed a method in psychology where the experimenter intentionally manipulates the independent variable (IV) to observe and determine if it has any impact on the dependent variable (DV). This allows researchers to establish cause-and-effect relationships and draw conclusions about the variables being studied.

Operationalisation refers to the process of defining a variable in a way that allows it to be effectively measured. This involves specifying what is meant by the variable and how it will be observed or quantified. By operationalising a variable, researchers can ensure that their measurements are reliable and valid, allowing for accurate analysis and interpretation of data. Therefore, the statement that operationalisation involves defining what is meant by the variable is true.

The experimental group is the group that carries out the experiment with the independent variable (IV) present. This means that they are exposed to the factor being tested, such as smoking in this case. Therefore, the statement "The experimental group is the group carrying out the experiment in which the IV is present, e.g., smoking" is true.

A field experiment is a type of research study that is conducted in a real-life setting, such as a playground, office, or shop. It can take place both indoors and outdoors, but the key characteristic is that it always occurs in a real-life situation. This distinguishes field experiments from other types of experiments that may be conducted in a controlled laboratory environment. Therefore, the statement that a field experiment always takes place in a real-life situation is true.

The matched pair design involves matching participants based on similar scores or specific personality traits and then splitting them into different conditions of an experiment. This design helps eliminate participant variables and order effects, leading to greater accuracy compared to independent measure design. Identical twins are considered the ultimate matched pairs.

A two-tailed/non-directional hypothesis predicts that there will be an effect on the dependent variable (exam performance) as a result of being bullied at school, but it does not specify the direction of the effect. This means that the hypothesis does not state whether being bullied will positively or negatively impact exam performance. Instead, it simply suggests that there will be some kind of effect. Therefore, the statement "Being bullied at school will affect exam performance" is consistent with a two-tailed/non-directional hypothesis.

The null hypothesis is a statement that assumes there is no relationship or effect between the variables being studied. In this case, the statement suggests that the null hypothesis predicts no observable effect on the dependent variable (DV). Therefore, the correct answer is true, as the null hypothesis assumes no effect on the DV.

Matched pair design is a research design where participants are matched with someone who has a similar score on a pre-decided test or displays a similar personality trait. This matching process helps to eliminate participant variables and ensures that the groups are as similar as possible. Identical twins are considered the ultimate matched pairs. After the matching process, the participants are split between two conditions in an experiment, which helps to remove order effects and provides greater accuracy compared to independent measure design.

Counterbalancing is the correct answer because it refers to a technique used in repeated measure design experiments where participants are split into groups and perform the conditions in alternating order. This helps to combat order effects such as boredom effect and practice effect. By counterbalancing the order of conditions, researchers can ensure that any effects observed are not due to the order in which the conditions were presented.

Quota sampling is indeed similar to stratified random sampling, as both methods involve dividing the population into sub-groups. However, in quota sampling, the researcher selects participants from within each sub-group based on certain pre-determined criteria or quotas. This allows for a more targeted and representative sample, as the researcher ensures that each sub-group is adequately represented in the sample. Therefore, the statement "Quota sampling is similar to Stratified Random Sampling, but the researcher will then pick participants from within each pre-identified sub-group" is true.

The Likert scale is a commonly used rating scale that measures the strength of a response or opinion. It typically consists of a range of options, such as a scale of 1 to 10, where respondents can indicate their level of agreement or disagreement with a statement. This scale allows for quantification of subjective data and provides a standardized way to measure attitudes, opinions, or perceptions. It is widely used in research and survey methodologies to gather and analyze data.

Replication in scientific experiments refers to the ability to repeat the experiment using the same procedures and obtain consistent results. This is important for ensuring the validity and reliability of scientific findings. By providing clear and detailed instructions, other researchers can replicate the experiment and verify the results, adding credibility to the original study. Therefore, the statement that replication requires easy-to-follow steps for consistent results is true.

Counterbalancing is the correct answer because it refers to a method used in repeated measure design experiments where participants are split into groups and perform the conditions of the experiment in alternating order. This helps to combat order effects such as boredom and practice effects, ensuring that the results are not influenced by the order in which the conditions are presented.

An unstructured interview is a type of interview where there is no predetermined set of questions or format. Instead, the interviewer engages in a free-flowing conversation with the interviewee, allowing for more flexibility and spontaneity. This type of interview allows for a deeper exploration of the interviewee's thoughts, experiences, and personality, providing a more comprehensive understanding of their suitability for the role. It also allows the interviewer to adapt and ask follow-up questions based on the interviewee's responses, leading to a more personalized and in-depth assessment.

The correct answer is participants undergo only one condition of the experiment and are randomly assigned to the experimental or control group. This design is good when there are only two groups and does not take participant variables into account. This is referring to an independent measure design, where participants are only exposed to one condition and are randomly assigned to groups. This design is useful when there are only two groups and helps to control for participant variables.

The correct answer is participants experience all conditions of an experiment one after the other, they are split into the same number of groups as there are conditions in the experiment. This design, known as a within-subjects design or repeated measures design, allows each participant to serve as their own control, eliminating participant variables. It is good for studying the effects of different conditions on the same group of participants. Counterbalancing is required to control for order effects. This design provides greater accuracy than independent measures design as it removes order effects and allows for direct comparison within participants.

Happens indoors in controlled laboratory conditions. Low ecological validity but allows experimenter to control situational and participant variables as much as possible.

This answer correctly identifies the independent measure design as the option that involves participants undergoing only one condition of the experiment and being randomly assigned to either the experimental or control group. It also mentions that this design is suitable when there are only two groups. Additionally, it acknowledges that this design does not take into account participant variables in each group.

Qualitative data refers to highly detailed, emotional data that is usually gathered through in-depth interviews, observations, or other similar methods. It focuses on understanding the subjective experiences, opinions, and perspectives of individuals. This type of data provides rich insights and allows for a deeper understanding of complex phenomena. In contrast, quantitative data involves numerical measurements and statistical analysis, aiming to quantify and generalize findings. Therefore, the given answer, "Qualitative data," correctly describes the type of data that is highly detailed and emotional, gathered from in-depth interviews, and so on.

The correct answer is the participants experience all conditions of an experiment one after the other, they are split into the same number of groups as there are conditions in the experiment. This design is known as a repeated measure design and is good for eliminating participant variables. Counterbalancing is required to ensure that the order in which the conditions are presented does not affect the results. This design allows for each participant to serve as their own control, increasing the accuracy of the results.

The experimenter effect refers to the influence that the characteristics and behavior of the experimenter can have on the participants' behavior in an experiment. This means that factors such as the experimenter's race, age, sex, and general behavior can impact how participants respond or behave during the study. Therefore, the given statement is true, as it accurately describes the concept of the experimenter effect.

Self-selected/volunteer sampling is the correct answer because it refers to a sampling method where individuals choose to participate in a study or survey. In this case, the participants responded to advertisements or requests for volunteers. However, this sampling method can lead to biased results because those who choose to participate may have different characteristics or motivations compared to the general population. Therefore, the sample may not be truly representative of the population, which can limit the generalizability of the findings.

The statement is false because the D.V. (dependent variable) is the variable that is being measured or observed in an experiment, not manipulated. The independent variable (I.V.) is the variable that is manipulated or changed by the experimenter.

The correct answer is that the participant's behavior is affected by the fact that they have already been through one or more conditions of the same experiment, meaning they may be more or less likely to behave in a certain way. This explanation aligns with the concept of the boredom effect, where participants may become bored or fatigued after performing the same task multiple times, leading to a change in their behavior. By using a repeated measure design and alternating the order of conditions, researchers aim to combat order effects such as the boredom effect and practice effect.

A structured interview is a type of interview where the interviewer asks a set of predetermined questions to the interviewee in a specific order. The questions are designed to gather specific information and are asked in a standardized manner to ensure consistency across all interviews. This type of interview allows for a systematic and objective evaluation of candidates as their responses can be compared directly. It also helps in reducing bias and ensuring fairness in the selection process.

The statement is false because the independent variable (I.V.) is not the variable being measured by the experimenter. The I.V. is the variable that is manipulated or changed by the experimenter to observe its effect on the dependent variable (D.V.), which is the variable being measured. The D.V. is the variable that is affected or influenced by the changes in the I.V.

A quasi/natural experiment is the most appropriate explanation because it involves conducting an experiment in a natural setting without manipulating the independent variable. This means that the researchers are observing and studying a phenomenon that occurs naturally, without any interference or control over the variables. In this type of experiment, the researchers take advantage of existing conditions or events to gather data and draw conclusions about cause and effect relationships. It is different from a field experiment, which involves manipulating the independent variable, and a laboratory experiment, which is conducted in a controlled environment.

The explanation for the given correct answer is that the boredom effect refers to the phenomenon where a participant's behavior is influenced by the fact that they have already experienced one or more conditions of the same experiment. This means that their behavior may be more or less likely to follow a certain pattern or respond in a specific way. The use of a repeated measure design in experiments helps to combat order effects such as the boredom effect by alternating the conditions that participants perform in, thus reducing the impact of previous conditions on their behavior.

Generalization is the act of drawing conclusions or making statements that can be applied to a larger population based on a smaller sample or set of observations. It involves inferring or extrapolating information from a limited number of cases to a larger group. In this context, generalization refers to the understanding that the views, results, or findings obtained from a small sample size, such as 10 people, cannot be reliably applied to the entire population. It recognizes the need for larger and more representative samples to ensure the validity and applicability of research findings.

Systematic sampling is the correct answer because it involves selecting participants from a population using a systematic method, such as choosing every tenth person on a list. This method ensures that the sample is representative of the population and reduces the chances of bias. It is a more structured approach compared to other sampling methods like random sampling, stratified random sampling, quota sampling, opportunity sampling, and self-selected/volunteer sampling.

A quasi/natural experiment is the correct answer because it is an experiment type that takes place in a natural setting and does not involve an independent variable (I.V.). In this type of experiment, the researcher observes and measures the effects of naturally occurring factors or events on the dependent variable (D.V.). Unlike a laboratory experiment, there is no manipulation of variables or control over the experimental conditions. Therefore, a quasi/natural experiment is the most suitable explanation for this scenario.

The independent measure design has several disadvantages. Firstly, it provides less control over participant variables, meaning that there is a higher chance of individual differences influencing the results. Secondly, this design requires a large number of participants to create different groups, which can be time-consuming and costly. Lastly, participant differences can indeed affect the data, leading to potential confounding variables. Therefore, all of the mentioned options are valid disadvantages of the independent measure design.

The practice effect refers to the phenomenon where participants perform better in subsequent conditions of the same experiment. This effect is observed when using a repeated measure design, where participants are split into groups and perform the conditions of the experiment in alternating order. By doing so, it helps to combat order effects such as boredom and practice effects. The participant's behavior is influenced by the fact that they have already experienced one or more conditions of the experiment, making them more or less likely to behave in a certain way. Therefore, all of the above statements accurately describe the practice effect.

The practice effect refers to the phenomenon where participants perform better in subsequent conditions of the same experiment. This effect is observed when participants have already been through one or more conditions of the experiment, causing their behavior to be influenced by their previous experience. It is important to use a repeated measure design in these experiments, where participants are split into groups and perform the conditions in alternating order to combat order effects such as boredom and practice effects.

The independent measure design has several disadvantages. Firstly, it provides less control over participant variables, meaning that there may be factors influencing the results that are not accounted for. Additionally, this design requires a large number of participants to make up different groups, which can be time-consuming and costly. Lastly, participant differences can have an impact on the data collected, leading to potential confounding variables. Therefore, all of the mentioned disadvantages apply to the independent measure design.

A confounding variable is an extraneous variable that affects one or more conditions of the experiment but not all. This means that it definitely affects the independent variable (IV) in some way. However, it does not necessarily cause an effect on the dependent variable (DV) or the outcome of the experiment. Therefore, the statement "True" accurately reflects this explanation.

One tailed/directional hypothesis predicts the direction of DV. Eg. Being bullied at school will decrease exam performance.

The correct answer is "Generalisation, replication, validity". These three conditions are essential for a valid experiment. Generalisation refers to the ability to apply the findings of the experiment to a larger population or real-world situations. Replication means that the experiment can be repeated by other researchers to ensure the reliability of the results. Validity ensures that the experiment measures what it intends to measure and that the results are accurate and meaningful. Therefore, these three conditions are crucial for ensuring the credibility and usefulness of an experiment.

Opportunity sampling refers to a non-probability sampling technique where the researcher selects individuals who are readily available and willing to participate in the study. In this method, the researcher takes advantage of the opportunity to include individuals who are easily accessible, such as stopping people in the street. However, this sampling method may introduce bias as the researcher's choice may be influenced by factors like personality or looks. Therefore, the correct answer is opportunity sampling.

The correct answer is "A list of questions to be asked. It standardises research." This answer is correct because an interview schedule refers to a predetermined set of questions that will be asked during an interview. Having a list of questions helps to standardize the research process as it ensures that all participants are asked the same questions, allowing for consistency and comparability in the data collected.

Validity: you must be measuring what you think you’re measuring. eg. Is there anything else causing behaviour of DV?

The matched pair design is advantageous because it reduces the impact of individual differences between participants, which can lead to more accurate results. Additionally, it helps to eliminate order effects, which occur when the order in which participants experience different conditions affects their responses. Lastly, the matched pair design is also useful for conducting misleading experiments, where participants are intentionally misled to study their reactions and behaviors. Therefore, the correct answer is "All of the above" as it encompasses all the advantages mentioned.

The matched pair design has the disadvantage of never being able to ensure that participants are perfectly matched. This is because it is almost impossible to find twins or individuals who are exactly alike in all relevant characteristics. Additionally, a large number of participants are needed to create two groups for comparison in this design. These factors make the matched pair design less practical and reliable compared to other research designs.

The matched pair design is advantageous for misleading experiments because it allows for the comparison of two similar individuals or groups, minimizing the influence of extraneous variables. Additionally, the design minimizes problems with individual differences by pairing participants based on relevant characteristics. Furthermore, the design eliminates order effects, as each participant is only exposed to one condition. Therefore, all of the given options are advantages of the matched pair design.

Quantitative data refers to numerical information that can be measured or counted. It can be easily represented using charts, graphs, or other visual representations. This type of data provides precise and objective information, allowing for easy analysis and comparison. Therefore, the answer "numerical" accurately describes the nature of quantitative data.

Predicts an effect on the DV.

The correct answer is "Cannot be used when participants HAVE to be different e.g. men and women" and "Problem of order effects means a need for counterbalancing". Repeated measure design is not suitable when participants need to be different, such as in studies comparing men and women. Additionally, this design can be challenging to measure accurately. Furthermore, the problem of order effects, where the order in which conditions are presented can influence results, necessitates the use of counterbalancing techniques to control for this potential bias.

A repeated measure design involves using the same participants for multiple conditions or treatments. One disadvantage of this design is that it cannot be used when participants have to be different, such as when studying the effects of gender. In such cases, it would be necessary to use a between-subjects design instead. Additionally, repeated measure designs can be difficult to measure accurately, as they require multiple measurements from the same participants. Furthermore, there is a problem of order effects, where the order in which the conditions are presented can influence the results. To address this issue, counterbalancing is needed to ensure that each condition is equally distributed across participants. Therefore, the correct answer is that all of these are disadvantages of a repeated measure design.

The correct answer is "Eliminates individual differences of participants" and "More data with small sample". In a repeated measure design, the same group of participants is tested under different conditions or at different time points. This design helps eliminate the individual differences among participants as each participant serves as their own control. Additionally, because the same participants are tested multiple times, more data can be collected with a smaller sample size, leading to more statistical power and efficiency in the study.