RESEARCH METHODS 2026

Added 3-4 terms OG

What is the aim?

A statement outlining the purpose of the investigation that is concise.
-Ensure the aim relates to the research question and other aims (if they are any)

What is a hypothesis?

A testable prediction about the relationship between two or more variables

How is a hypothesis reviewed?

Either supported or rejected, never proved!

What is a controlled experiment

An investigation to test the relationship between an IV and a DV whilst controlling all other variables.

What is a variable?

Something that can change (‘vary’) in amount or type & is measurable

What is a controlled variable?

Variables that are held constant to remove potential effects on the DV.

Independent variable (IV) (sometimes known as the treatment variable)

The variable that is systematically manipulated in order to test its effect on the D.V

dependent variable (DV) is

The variable the researcher measures to observe the effects of the IV.

Operationalising variables

Refers to specifying exactly how the variables will be manipulated or measured in a controlled experiment.

Lists the types of research methods

Correlational Methods

Experimental Methods
Descriptive Methods: observational studies, self reports, case studies

Experimental: laboratory experiments, field experiments
Non-experimental: questionnaires, interviews, simulation studies, case studies, observational studies, correlational studies

What is a correlational study?

Measures if there is a relationship between variables
no manipulation from the researcher including controlling the setting.

List the types of descriptive methods:

Self reports
Observational studies
Case studies

SOC

List the types of experimental methods

Laboratory experiments, field experiments

List the types of non-experimental research methods

Questionnaires

Interviews
Simulation studies.

Case studies

Observational studies
Correlational studies

QIS COC
(Quizz cook)

What is a self-report?

A participant’s answers to questions presented by the researcher.

What is an oberservational study?
+ves & -ves

Involves the collection of data by watching and recording behaviour without any intervention or manipulation of what is being observed.

Longitudinal study

Cross-sectional study

+’s:

Removes EV: artificiality (effect of unnatural environment)

-’s:

observer bias

What is a case study.

An intensive, in-depth investigation of behaviour, activity, event or problem of interest in an individual, group, organisation or situation.

What is cross-sectional method

Observational study

Involes analysing data from a population at one specific point in time.
Variables are not manipulated.

What is a longitudinal study?

Observational study
Involves repeated observations of the same individuals over a long period of time.

What is the population?

The entire group of people relevant to the research, that the sample is then drawn from.

What is the point of the population?

In order to generalise (apply) the results from an investigation to a wider relevant group.

What is the sample?

A subset or part of the population that is selected for research purposes

What is sampling

The process of selecting a part of the population for research.

What is random sampling? and examples

Sampling technique
Ensures every member of a population has an equal chance of being selected for the sample.

Pulling names out of a hat
Using wheel spinner

What is stratified sampling?

Dividing the research population into various subgroups (strata) based on relevant characteristics, then selecting participants in proportion to how they appear, so that each subgroup is represented.

what is convenience sampling?

Involves selecting the most readily available members of the population

Advantages of convenience sampling

Advantages: most time-effective and can be cost-effective

Disadvantages: The most likely sampling technique to create an unrepresentative sample (likely to share similar characteristic)

making generalisation harder

Stratified sampling advantages/disadvantage

Advantages:
Most likely to produce a representative sample.

Disadvantage:
Can be time consuming & expensive
May be demanding for researcher to select most appropriate sample

Random sampling advantages/disadvantages

Advantages:

Sample may be more representative than convenience sampling.

Reduces researcher bias

Can be representative if the sample is large

Disadvantages:
May be time consuming
If the sample is small may not be representative

What is an extraneous variable?

A variable other than the IV that produces an unwanted effect, by potentially causing a change to the DV

What is a confounding variable?

A variable other than the IV that has had an effect on the DV and cannot be separated from the IV.

EVs may turn into confounding variables if they have a big impact on the interpretation of results.

Beneficence

ETHICAL CONCEPT
Trying to maximise benefits and minimise risks and harms

Integrity

ETHICAL CONCEPT
Commitment to add to public knowledge
Use honest reporting

Making study available to scrutiny

😱

Justice

ETHICAL CONCEPT:
Fair consideration of competing claims
No unfair burden on a certain group
Fair access to the benefits of the study

Non-maleficence

ETHICAL CONCEPT
Involves avoiding the causation of harm

Respect

ETHICAL CONCEPT:
Involves considering the rights of participants and that they are protected and empowered

List the ethical concepts

Beneficence

Respect
Integrity

Non-maleficence
Justice

BRINJ

Ethical guidelines

(Use of) Deception

Voluntary participation

Informed consent procedures

Debriefing

Withdrawal rights

Confidentiality

DVIDWC

Confidentiality

ETHICAL GUIDELINE:
All of a participant’s personal information and results are kept anonymous

Debriefing

ETHICAL GUIDELINE:

Ensures that at the end of an experiment, the participant leaves understanding the experimental aim, results and conclusions.

Informed consent procedures

ETHICAL GUIDELINE:

Before agreeing to be apart of a study participants should understand the nature and purpose of the experiment, including potential risks

Use of deception in research

ETHICAL GUIDELINE:

Deception can only be used if participants knowing the true purpose of the experiment may affect their behaviour whilst participating in the study, and the subsequent validity of the experiment.

Voluntary participiation

ETHICAL GUIDELINE:

Ensures that no coercion or pressure is put on the participant to partake in an experiment, and they freely choose to be involved.

Withdrawal rights

ETHICAL GUIDELINE:
Involves a participant being able to leave an experiment at any time during or after the conclusion of an experiment, without penalty.

What is reliability

Refers refers to the extent to which a measure

produces results that are consistent, dependable and stable.

REPEATABILITY:
Relates to the extent results are consistent under the same conditions

REPRODUCIBILITY: refers to how the consistent results are

under changed experimental conditions.

What is validity

Refers to the extent an investigation measured what it intended to.

Means the results represent the population the sample was drawn from.

Internal validity

Relates to how well the study was conducted
Additionally if the study investigated what it set out to/claims to have

External validity

Relates to the applicability of the results, to see if results can be applied beyond the study’s sample, to the wider population.

generalisation

When the research findings are applied to the the broader population.

Made when results:
Statistically significant
Sample is representative of population

Method of sampling is appropriate
Variables controlled

No know sources of error or biases

SS M V N

what is included in a good hypothesis

Variables that can be observed & measured
One sentence
Can be supported or refuted

States the existence and direction of a relationship

A good aim

Clear and concise
One sentence
Relates to research problem/question

Describes purpose of investigation

List the 7 steps of research

1. Identify research problem

2. Formulate hypothesis

3. Design the Method

4. collect the data

5. analyse the data

6. Interpret the results

7. Report the findings

What is Identify the research problem

Step 1 in research
Identify topic of interest

conduct a literature search- read relevant research articles

Develop research question

Step 2 in research

Formulate a hypothesis

Design the Method

Step 3 in research

Determine how the researcher will test the hypothesis.

• WHO will participate

• WHAT they will do

• WHAT conditions

• HOW to sample them

• HOW many participants

Minimise any unwanted variables

Step 4 in research

Collect the data

To measure participants performance, opinions or results.

Analyse the data

Step 5 in research
Researcher must make sense of data by:
organising, representing,raw data, summarising,in a logical manner

ORS

Raw data

the actual data collected from a study.

Step 6 in research

Interpret the results
Involves forming conclusions about what the data shows

Inferential statistics

Stats that allow you to make inferences and conclusions about the data

Report the findings

Step 7 in research
Psychological research is conducted so it can shared.
Prepare a report, so the public can benefit from the findings.

Participant allocation

Once participants have been selected for a study, they must be allocated to groups within the study

Random Allocation

Ensures every member in the sample has equal chance of being assigned to groups in the experiment

Experimental group

group(s) exposed to the experimental conditions

Control group

THe groups that is exposed to the control condition, where the IV is absent.

3 Experimental design options

Between subjects
Within subjects
Mixed subjects

Between subjects

2 different groups of participants are compared

672 × 307

Types of between subjects experimental dsign

Independent-groups design (random allocation)
The matched-participant design (pairing and divide)

Independent-groups design
+ Advantages and Disadvantages

Experimental research design: Between subjects:
Involves randoming allocating members of the sample to either the control group or experimental group

+ves:
Quick and easy design
Enables large number of particiapnts

in a timely & cost-effective way

-ves:

may be participant differences across groups

The matched Participant design
Advantages and limitations

Experimental research design: Between subjects

Seeks to eradicate participant differences across groups.
Involves pairing each participant based on a characteristic they share

then randomly allocating one to the control group and one to the experimental group .

Advantages:
Minimise extraneous variables by spreading participant characteristics

limitation:
involves pre-test
time consuming
if one participant leaves so to does the other.

Participants are not identical.

Within subjects design
Advantages and limitations

The same participants are used in both the control and experimental groups, or all the treatment conditions (if there is no control group)

Advantages:

Identical characteristics and abilities, no participant differences

Limitations:

Order effects

Order effects

When there is a change in results due to the sequence of tasks being completed.

Increased performance due to knowledge or experience
OR
Decrease due to boredom or fatigue.

How to minimise order effects?

Counterbalancing!
Occurs in within subjects designs

Involve dividing the group of participants in half and arranging the order so it’s different for each group.

Half will experience control first then experimental and the opposite for the other group

Placebo

A fake or false treatment used so none of the participants know if they are exposed to the experimental condition.

+ves:

reduces impact of placebo effect

Placebo effect

Occurs when there is a change in a participant’s behaviour due to their expectations about the treatment.

Single-blind procedure

When the participants do not if they are in the control or experimental group(s)

-placebos used, reducing participant expectations on the results
-experimenter affect may still impact particiaptns

Experimenter effect

Occurs when there is an unintentional change in participants due to the experimenters influence

Body language, verbal cues, preferential (better) treatment

Also known as demand characteristics, where the experimenters behaviour inadvertently causes a demand for participants to perform as the experiment predicts.

Double blind procedure

Neither participants not the experimentor know which participants have been alocated to the control and experimental groups.

+ves:

reduce impact of experimenter effect on results

-ves:

involves another person knowing who’s in what group

Difference between a correlation and controlled experiment

Controlled: seeks to establish a cause-and-effect relationship exists
Correlational: seeks to show two or more variables are related

Primary Data

New research
Data a researcher gathers themselves during a current study

Secondary data and what can it be used for

When a researcher uses previous research or knowledge in their own study.
Basis for future predictions

Used for data modelling

What does data modelling allow?

Predicted pattern to be considered, so a change can be prevented or mitigated.

Subjective vs Objective Data

Subjective data: based on opinions
Objective data: observable and measurable

What is subjective data

+ve & -ve

Based on opinion, from observations or self reprots.
Comprises: personal information

+’s

can provide great insight into a person’s opinions or beliefs

-’s

Difficult to compare and analyse

Objective Data

data that can be observed and measured

+’s

easily analysed and compared

Minimise biases from subjectivity

-’s
Doesn’t provide reasoning behind the data

Qualitative vs quantitative

Qualitative:
describe changes in quality

Quantitative:
Opinion based

Qualitative Data

Describes changes in the quality of behaviour, often expressed in words
Opinion based
+’s
participants can provide great insight

-’s
Difficult to categorise os statistically analyse or compare
open to personal, observer, researcher biases

Quantitative data

Collected through systematic and controlled procedures

Typically presented in numerical or categorical form

+’s
can be statistically analysed and readily measured (Similar to objective data)

-’s
restrict participants answers

provides no insight to reasoning behind data

Mixed Methods Research

incorporates both quantitative and qualitative into research

Results strengthened because quantitative data is paired with explanations using qualitative data.

The Different Types of Data

Primary: Data gathered in present study
Secondary: Previous research or knowledge
Subjective: Based on opinion from self reports & observations
Objective: Observable and measurable data
Qualitative: Describes changes in behaviour, often expressed in words
Quantitative: collected systematically, presented in numerically
Continuous: real values exist between each data point
Discrete: categories have no relationship to each other

Descriptive Statistics list

Percentages
Measures of Central Tendency:
mean

median

mode
Variability

Percentages illustrate:

the proportion of the sample that displays a particular behavior.
number × total ÷ 100

+’s
Quick and effective way to compare group results

Central tendency

Involves calculations that show how typical scores fall in the data set.

3 measures of Central Tendency:

Mean: all scores are + then ÷ by total

-’s greatly influenced by outliers, skewing data

Median: middle number in ordered data.
+’s not affected by outliers

Mode: most commonly occurring number in data set.

+’s useful for visualising most often score

-’s unreliable for small samples

Variability

How data is spread

E.g:

Range: lowest score - highest score
Standard deviation: Looks at how far each piece of data deviates/differs from the mean

Low SD = scores are clustered around the mean = low variability
High SD = scores are spread from the mean = high variability

Why use descriptive statistics +’s & -’s

+’s
Organisation

-”s
Do not account for errors

Do not establish cause and effect relationship
Need more data to draw conclusions

Frequency distribution table

Simple way of organising data if there is a large amount of data.

Categories being compared place in one column, in class intervals
Count how many times data fits into each category referred to as frequency

A graph enables,

large amounts of information to be neatly organised and summarised
can show how one variable relates to another

Types of graphs

Histogram:
class intervals on x axis, frequency on y axis,
Bars touch as data is continuous

can be made from frequency distribution table

Frequency polygon:
adapted histogram

type of line graph that joins midpoints of histogram

begins and ends on x-axis.

Line graph:

Single line that connect points that relate to one another

Continuous data

Real values exist between each data point

data is on a continuum

Discrete data

the data is unrelated, not on a continuum