Research Methods One

Not quite everything. (!?) Honess

What is a hypothesis?

A hypothesis is a testable statement about the relationship between two or more Variables. It is an educated guess or a proposed explanation for a phenomenon that can be tested through experimentation or observation

What is an aim?

An aim is a statement that describes what a study intends to achieve. It outlines the overall purpose or goal of the research, often in a broad sense.

What is the Experimental Method?

Manipulating an Independent Variable, to measure the effect on the Dependant Variable

What is H₀ ?

Null hypothesis.

What is H₁ ?

Alternate Hypothesis.

What are the 4 types of experiment?

Field, Laboratory, Natural, Quasi.

What is a Field Experiment?

A research method conducted in a natural, real-world setting instead of a lab, where researchers manipulate an independent variable to measure its effect on a dependent variable

What are the strengths of Field Experiments?

• High ecological validity: The findings are more likely to be generalisable

• Natural behaviour: Participants' behaviour is more natural and less affected by the artificiality of a laboratory.

• Causal inference: Random assignment helps establish a cause-and-effect relationship between variables.

What are the weaknesses of Field Experiments?

• Less control: Researchers have less control over extraneous variables.

• Ethical concerns: Participants might not be able to give informed consent if they are unaware they are in a study.

• Difficult to replicate: The unpredictable nature of real-world settings can make it hard to replicate the experiment.

What is a Laboratory Experiment? 

A research method conducted in a highly controlled environment where researchers manipulate one or more independent variables to measure their effect on a dependent variable.

What are the strengths of Laboratory experiments?

• High internal validity: The tight control over variables means that a clear cause-and-effect relationship between the IV and DV can be established.

• Replicability: The controlled, standardized procedures make it easier for other researchers to replicate the study and verify the findings. 

What are the weaknesses of Laboratory experiments?

• Low external or ecological validity: The artificial environment may not reflect real-world settings, making it difficult to generalize the results to everyday situations.

• Potential for artificiality: Participants might change their behaviour because they are aware they are being studied, a phenomenon known as demand characteristics

What is a Natural experiment?

an observational study where researchers leverage a naturally occurring event or pre-existing situation to investigate the effect of an independent variable (IV) on a dependent variable

What is are the strengths of Natural experiments?

• High External Validity: These studies take place in real-world, natural settings, the findings often have high ecological validity and can be more readily generalised to the wider population.

• Reduced Bias: Participants are often unaware they are part of a study, which minimizes the demand characteristics

• Cost-Effectiveness: Natural experiments can be a pragmatic and cost-effective research design, especially if relevant data is already available from national sources or existing records.

• Real-World Application: They provide a useful tool for evaluating the effectiveness of actual policies and interventions in complex social and political conditions.

What are the weaknesses of Natural experiments?

• Difficulty Inferring Causation: It is difficult to establish a clear cause-and-effect relationship because the researcher has little or no control over extraneous or confounding variables.

• Lack of Control: The researcher cannot manipulate the IV or randomly assign participants to conditions, which lowers internal validity.

• Replication Difficulties: Due to the unique nature of naturally occurring events, it can be extremely difficult to replicate the study conditions.

• Potential for Bias: Even without demand characteristics, other forms of bias can occur, such as observer bias or sample bias.

• Data Limitations: Researchers often rely on retrospective data collected for other purposes, which may be inaccurate, incomplete, or difficult to access.

What is a Quasi experiment?

A type of research method that aims to establish a cause-and-effect relationship between variables but lacks random assignment of participants to groups.

What are the strengths of Quasi experiments?

• High External Validity: Because they are often conducted in real-world, natural settings rather than artificial laboratory environments, the findings tend to be more generalizable to the broader population and other contexts.

• Study of Naturally Occurring Events: Researchers can study the effects of naturally occurring events or pre-existing conditions that cannot be manipulated in a true experiment.

• Cost-Effectiveness and Efficiency: These designs are often less expensive and time-consuming than true experiments, requiring fewer resources and potentially smaller sample sizes.

• Higher Internal Validity than Non-Experimental Research: While lower than true experiments, quasi-experiments allow for more control over confounding variables. 

What are the weaknesses of Quasi experiments?

• Lower Internal Validity: The primary weakness is the inability to definitively establish a causal relationship due to the lack of random assignment.

• Risk of Confounding Variables and Bias: There is a higher likelihood of confounding environmental and extraneous variables influencing the results.

• Difficulty Ruling Out Alternative Explanations: The lack of control makes it challenging to rule out alternative explanations for the observed results, as any differences between groups could be due to pre-existing disparities rather than the independent variable.

• Reliance on Retrospective Data: Retrospective data, often used in some quasi-experimental designs, can be inaccurate, incomplete, or difficult to access, potentially affecting the reliability of the findings.

• Statistical Complexity: To account for potential biases and confounding variables, quasi-experimental studies may require the use of advanced statistical techniques such as multiple regression or propensity score matching.

Which types of experiments have high levels of Complexity?

Field, Natural, and sometimes Quasi

Which types of experiments have lower levels of complexity?

Laboratory, sometimes Quasi

Which types of experiments have high levels of Variable Control?

Laboratory Experiments

Which types of experiments have low levels of Variable Control?

Field, Natural, sometimes Quasi

Which type of experiments have high levels of Internal Validity?

Laboratory

Which types of experiments have low levels of Internal Validity?

Field, Natural, Quasi

Which types of experiments have high levels of External Validity?

Field, Natural, sometimes Quasi

Which types of experiments have low levels of External Validity?

Laboratory, sometimes Quasi

Which types of experiments have high levels of Demand Characteristics?

Laboratory, Natural, sometimes Quasi

Which type of experiments have low levels of Demand Characteristics?

Field

Which types of experiments have high levels of Realism?

Field, Natural, Quasi

Which type of experiments have low levels of Realism?

Laboratory

What is Non-Directional?

Increase/Decrease of the outcome is not specified.

What is Directional?

Increase/Decrease of the outcome is specified.

Are Extraneous Variables wanted?

No.

What is an extraneous variable?

Any Variable, other than the Independent Variable, that may affect the Dependant Variable. They are nuisance variables that don’t vary systematically with the Independent Variable.

What are confounding variables?

Any variable, other than the Independent Variable, that may effect the Dependent Variable. We cannot be sure of the true source of the changes. They vary systematically with the Independent Variable.

What are Demand Characteristics?

Any cue from the researcher or environment that may be interpreted as the purpose of the investigation.

What can Demand Characteristics lead to?

Participants changing their behaviour, making the findings less valid.

Investigator Effects

Any effect of the Investigator’s behaviour on the research outcome. This varies from the design of the study, to the selection of and interaction with participants during the study.

What is the Please-You Screw-You Effect?

Participant(s) conscious bias caused by known Demand Characteristics.

What is Randomisation?

The use of chance in order to control the effects of bias when choosing participants. 

What is Standardisation?

Using exactly the same formalised procedures and instructions for all participants in a research study.

What is Social Desirability Bias?

A type of response bias that is the tendency of survey respondents to answer questions in a manner that will be viewed favourably by others. It can lead participants to over-report 'good' behaviours or under-report 'bad' behaviours.

What is the Experimental design?

A systematic approach to planning and conducting scientific experiments to test hypotheses and establish cause-and-effect relationships between variables.

What is the Repeated Measures design?

An experimental method in which the same participants are used in all conditions of an experiment

What are the advantages to the Repeated Measures design?

Controls Individual Differences: Eliminates participant variables as a potential source of error.

Greater Statistical Power: By reducing variability caused by individual differences, the design increases the sensitivity to detect the true effects of the independent variable.

Efficiency and Cost-Effectiveness: Requires fewer participants and resources.

What are the issues with the Repeated Measures design?

Order Effects: Prior exposure to one condition can influence performance in subsequent conditions.

Demand Characteristics: Participants might guess the study's purpose after experiencing multiple conditions, potentially changing their behaviour.

Not Always Feasible: Not suitable for all research questions, especially if the first treatment has a lasting or irreversible effect that would interfere with subsequent conditions.

What is the Independent Group design? 

An experimental method where different participants are used in each condition of the experiment.

What are the advantages to the Independent Group design?

No order effects: Participants only take part in one condition, so there are no practice, fatigue, or boredom effects. This improves internal validity because performance is not influenced by having done the task before.

Lower risk of demand characteristics: Participants are less likely to guess the aim, as they only experience one level of the IV. This also increases validity.

What are the disadvantages to the Independent Group design.

Participant variables may confound results: Differences between participants (e.g., intelligence, motivation, personality) may affect the DV. This reduces internal validity because differences between conditions may be due to individual differences, not the IV.

Requires more participants: Every condition needs a new group of people. This makes the design more time-consuming, expensive, and impractical for small samples.

What is the Matched Pairs design?

An experimental design where participants are paired based on relevant characteristics, and each member of the pair is placed in a different condition.

What are the advantages to the Matched Pairs design?

Reduces participant variables: Participants are matched on relevant characteristics (e.g., age, IQ). This increases internal validity compared to independent groups because differences between conditions are more likely due to the IV.

No order effects: Like independent groups, participants only take part in one condition. Reduces practice/fatigue effects and demand characteristics.

What are the issues with the Matched Pairs design?

Very time-consuming and difficult to match accurately: Finding closely matched pairs can be slow and often requires pre-testing.

Matching is never perfect: Even if participants are matched on some variables, they can still differ in ways that influence the DV. This can reduce internal validity.

Requires more participants: As with independent groups, you need different people for each condition, meaning larger samples.

What is Sampling?

The process of selecting a group of participants from a target population so that they can take part in a study.

What are the types of Sampling Methods?

Opportunity, Random, Stratified, Systemic, Volunteer.

What is Opportunity Sampling

Selecting participants who are conveniently available at the time of the study.

What are the strengths of Opportunity Sampling?

Quick and easy: Participants are chosen because they are readily available, so it is fast and practical, making it useful for student or small-scale research.

Cost-effective: No need for a sampling frame or complex recruitment, so it is cheap and efficient.

What are the weaknesses of Opportunity Sampling?

Unrepresentative sample: The sample is drawn from people who happen to be available, which may not reflect the wider target population. This reduces population validity.

High risk of researcher bias The researcher chooses who is “available”, which may unintentionally lead to selecting certain types of people. This reduces internal validity.

What is Random Sampling?

A method where every member of the target population has an equal chance of being selected to take part in the study.

What are the Strengths of Random Sampling?

It is unbiased, as selection is based on chance rather than researcher choice. It increases the representativeness of the sample, which can improve the generalisation of findings to the target population.

What are the weaknesses of Random Sampling?

• Can be difficult and time-consuming if the target population is large.

• Might still produce an unrepresentative sample by chance.

What is Stratified Sampling?

Dividing the target population into subgroups (strata) based on important characteristics, then randomly selecting participants from each subgroup in proportion to their presence in the population.

What are the strengths of Stratified Sampling?

• Produces a highly representative sample because key variables are proportionately included.

• Allows for more accurate generalisation to the target population.

What are the weaknesses of Stratified Sampling?

• Time-consuming to identify and divide the population into strata.

• Not all relevant characteristics can be identified, so complete representation is hard to achieve.

What is Systemic Sampling?

Selecting every Nth person from a list of the target population after choosing a random starting point.

What are the strengths of Systemic Sampling?

• Simple and efficient method.

• Because the starting point is random, it can be fair and unbiased.

What are the weaknesses of Systemic Sampling?

• Could still be unrepresentative if the list has a pattern that accidentally coincides with the sampling interval.

• Requires a complete list of the population.

What is Volunteer Sampling?

Participants self-selecting to take part after seeing an advert, poster or online request.

What are the Strengths of Volunteer Sampling?

• Easy and convenient for researchers.

• Often results in participants who are motivated and willing to take part.

What are the weaknesses of Volunteer Sampling?

• High risk of volunteer bias (e.g., certain personality types more likely to volunteer).

• Sample may be unrepresentative, reducing generalisability.

What are Ethics?

Moral principles and guidelines that ensure research is conducted in a way that protects participants’ rights, dignity and well-being.

Where do Ethical issues arise from?

When there is a conflict between the researcher’s aims and the participants’ rights.

What is Deception?

When participants are deliberately misled or not given full information about the true aim of the study, often to prevent demand characteristics.

How can Deception be avoided?

• By giving participants full information about the study’s aim and procedures.

• Using alternative designs that do not require misleading participants.

What is Informed Consent?

Participants are fully informed about the nature, purpose and procedures of the study and agree to take part.

How can Informed Consent be upheld?

• Providing a consent form with clear information.

• Allowing participants to ask questions.

• Reminding them of their right to withdraw at any time.

What is Privacy & Confidentiality?

• Respecting a participant’s right to control personal information.

• Confidentiality means keeping a participant’s data and identity protected and not sharing it without permission.

How can Privacy & Confidentiality be upheld?

• Keeping data anonymous or using codes instead of names.

• Storing data securely.

• Only collecting information that is necessary.

What is Protection from Harm?

Ensuring participants are not exposed to physical or psychological harm, beyond what they would normally experience in everyday life.

How can Protection from Harm be upheld?

• Conducting a risk assessment before the study.

• Stopping the study if distress occurs.

• Providing debriefing and support afterwards.

What is a Pilot Study?

A small-scale trial run of the main research study.

What are the aims of a Pilot Study?

• To check whether procedures, materials, and measurements work as intended.

• To identify and fix problems or confusions before the full study.

• To ensure the study is feasible and valid.

Why do we use Pilot Studies?

To identify flaws in the procedure and improve the main study.

What is a Single Blind design?

Only participants do not know the true aim or condition they are in.

What is a Double Blind Design?

Neither the participants nor the researchers interacting with them know the conditions.

What are Self-Report techniques?

Methods where participants directly provide information (e.g., questionnaires, interviews).

What are Questionaries

Written sets of questions used to gather data from many people efficiently.

What are the strengths of Questionairres?

• Can gather large amounts of data quickly

• Cost-effective

• Often produce quantitative data that is easy to analyse

What are the weaknesses of Questionairres?

• Risk of social desirability bias

• Misunderstood questions

• Low response rates

What is an Unstructured Interview?

An informal, flexible interview with open-ended questions.

What is a Structured Interview?

Standardised, pre-set questions asked in a fixed order.

What is a Semi-Structured Interview?

Mix of set questions and open questions that allow exploration of answers.

What is Quantitative Data?

Numerical data.

What is Qualitative Data?

Descriptive, non-numerical data.

What kind of Data has high internal validity?

Qualitative data (rich detail, captures meaning).

What kind of data has high external validity?

Quantitative data (can be generalised more easily).

What kind of Data is better for finding patterns?

Quantitative data.

Which kind of Data is subjective?

Qualitative data.

Which kind of Data is objective?

Quantitative.

Which kind of Data has a higher investigator bias issue risk?

Qualitative data (interpretation can be influenced).