Scientific Process

Aim

A general statement about what the researcher intends to investigate.

Hypothesis

A precise, testable statement about the expected outcome of a study.

Difference between Aim and Hypothesis

An aim is a general research intention and a hypothesis is a specific prediction to be tested.

Directional Hypothesis

Predicts the direction of the effect (e.g. Group A will score significantly higher than Group B).

Non-Directional Hypothesis

Predicts that there will be a difference but does not state the direction.

Population

The larger group of people the researcher is interested in studying.

Sample

A smaller group selected from the population to take part in the study.

Random Sampling

Every member of the population has an equal chance of being selected.

Additional Strengths of Random Sampling

Reduces selection bias results are more likely to be generalisable.

When do you use directional hypothesis?

You use a directional hypothesis when there is clear theoretical or previous research evidence suggesting the direction of the expected effect or relationship.

Additional Weaknesses of Random Sampling

Difficult to access full population list, still possible to get unrepresentative sample by chance.

Strengths of Random Sampling

Unbiased and representative if large enough, Reduces selection bias, results are more likely to be generalisable.

Additional Strengths of Random Sampling

Reduces selection bias, results are more likely to be generalisable.

Additional Weaknesses of Random Sampling

Difficult to access full population list, still possible to get unrepresentative sample by chance.

Weaknesses of Random Sampling

Time-consuming, may not be truly random.

Additional Strengths of Random Sampling

Reduces selection bias, results are more likely to be generalisable.

Additional Weaknesses of Random Sampling

Difficult to access full population list, still possible to get unrepresentative sample by chance.

Systematic Sampling

Participants selected using a fixed interval from a list (e.g. every 5th person).

Stratified Sampling

Participants are selected proportionally from strata (subgroups) in the population.

Opportunity Sampling

Participants selected based on availability and willingness.

Strengths of Opportunity Sampling

Quick and easy convenient and cost-effective.

Weaknesses of Opportunity Sampling

High risk of sampling bias not generalisable.

Volunteer Sampling

Participants self-select by responding to an advert or request.

Strengths of Volunteer Sampling

Ethical participants give informed consent, easy to obtain sample.

Weaknesses of Volunteer Sampling

May attract a biased sample only certain personalities volunteer.

Sampling Bias and Generalisation

Sampling bias occurs when a sample is not representative, it limits generalisability of findings.

Repeated Measures Design

Same participants take part in all conditions of the experiment.

Additional Strengths of Repeated Measures

Controls for participant variables, increases statistical power due to fewer participants.

Additional Weaknesses of Repeated Measures

Order effects can distort results, requires counterbalancing.

Independent Groups Design

Different participants take part in each condition.

Additional Strengths of Independent Groups

Avoids order effects, no contamination of conditions.

Additional Weaknesses of Independent Groups

Participant variables may confound results, more participants needed.

Matched Pairs Design

Participants are matched on key variables and assigned to different conditions.

Additional Strengths of Matched Pairs

Reduces participant variables without order effects, useful when repeated measures not suitable.

Additional Weaknesses of Matched Pairs

Time-consuming and costly, difficult to perfectly match participants.

Strengths of Repeated Measures

Fewer participants needed, controls for participant variables.

Weaknesses of Repeated Measures

Order effects like fatigue or practice.

Strengths of Independent Groups

No order effects.

Weaknesses of Independent Groups

Participant variables may affect results.

Strengths of Matched Pairs

Reduces participant variables.

Weaknesses of Matched Pairs

Time-consuming and difficult to match perfectly.

Behavioural Categories

Clearly defined behaviours to be observed and recorded.

Event Sampling

Recording every instance of a particular behaviour during the observation period.

Strengths of Event Sampling

Good for recording infrequent behaviours, provides detailed insights.

Weaknesses of Event Sampling

May miss behaviours if events happen too frequently or simultaneously.

Time Sampling

Observations made at set time intervals.

Strengths of Time Sampling

Reduces data overload, allows manageable observation.

Weaknesses of Time Sampling

May miss key behaviours between observation intervals.

Open Questions

Allow respondents to answer in their own words produce qualitative data.

Strengths of Open Questions

Provides rich qualitative data allows deeper understanding.

Weaknesses of Open Questions

Harder to analyse may lead to irrelevant information.

Closed Questions

Have fixed responses, produce quantitative data.

Strengths of Closed Questions

Easy to quantify and analyse statistically increases reliability.

Weaknesses of Closed Questions

Limits depth of response may not reflect participants true feelings.

Designing Questionnaires

Ensure questions are clear, unbiased, and relevant.

Structured Interview

Uses pre-determined questions in a fixed order.

Unstructured Interview

More flexible, allowing deeper exploration of topics.

Independent Variable (IV)

The variable that is manipulated by the researcher.

Dependent Variable (DV)

The variable that is measured to see the effect of the IV.

Extraneous Variables

Other variables that could affect the DV and should be controlled.

Confounding Variables

Variables that actually affect the DV, obscuring the effect of the IV.

Operationalisation

Defining variables in a measurable, testable form.

Random Allocation

Participants are randomly assigned to experimental conditions.

Counterbalancing

Used in repeated measures to reduce order effects.

Randomisation

Using chance to control for bias when designing materials or deciding order.

Standardisation

Keeping procedures the same for all participants.

Demand Characteristics

Participants change their behaviour based on cues about the study's purpose.

Investigator Effects

When a researcher's expectations influence participants' behaviour.

Ethics

Moral guidelines governing research with human participants.

BPS Code of Ethics

a set of guidelines published by the British Psychological Society to ensure that psychological research is conducted in an ethical and responsible manner.

What are the 4 main ethical principles In the BPS?

Respect, competence, Responsibility and integrity

Dealing with Ethical Issues

Includes informed consent, right to withdraw, debriefing, protection from harm.

Reliability

The consistency of a research study or measuring test.

Inter-Observer Reliability

The extent to which different observers produce consistent results.

Improving Reliability

Train observers, use operational definitions, pilot studies, standardised procedures.

Validity

The extent to which a test or study measures what it claims to measure.

Ecological Validity

The extent to which findings can be generalised to real-life settings.

Assessing Validity

Use concurrent validity, face validity, or compare with other measures.

Improving Validity

Use standardised procedures, control extraneous variables, ensure realism

What is content analysis?

a research technique used to analyse qualitative data by converting it into quantitative or thematic data.

Strengths of content analysis

Can convert rich qualitative data into quantifiable results, Can be used with secondary data

Weaknesses of content analysis

May be subjective depending on how categories are defined, Can miss context or deeper meaning in the data