Psych - Research Methods (copy)

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Investigation aim

Investigation aim

The purpose of a study (includes IV, DV)

E.g To investigate the influence of caffeine consumption on memory performance.

Investigation question

The question that is to be solved by the study

E.g Does caffeine consumption influence memory performance?

Independent variable

The variable that is manipulated/altered in some way by the researcher to measure its effect on the DV

Dependent variable

The variable that is used to observe and measure the effects of the IV

Operationalising “does caffeine consumption increase memory performance?”

Operationalised IV: 5 cups of caffeine (in the form of coffee) or no cups of coffee

Operationalised DV: memory performance on a test of 20 questions

Controlled experiment

An investigation methodology that aims to test the effetcs of an IV on a DV, with all other variables controlled

Extraneous variables

Variables other than the independent variable that may have an unwanted effect on the dependent variable and results

Controlled variables

Variables that are held constant to ensure that the only influence on the dependent variable is the independent variable

Confounding variables

Unwanted variables that affect the DV and results in an investigation, and it cannot be determined whether the IV or ___ caused the change in the DV

Hypothesis

A statement outlining the probable outcomes of an investigation

Hypothesis template

It is hypothesised that (IV - experimental group) will have a (strength/direction) (DV) compared with (IV (control group)

E.g It is hypothesised that healthy adults who consume caffeine will show an increase memory performance compared with those who did not consume caffeine.

Population

The wider group of people that a study is investigating

Sample

The smaller group of people selected from the population who will be participants in the investigation

Stratified sampling

The population is first divided into subgroups, and participants are randomly selected from each subgroup, in the proportion that they appear in the population

Random sampling

Involves selecting participants from the population in such a way that each member of the population has an equal chance of being selected to participate in the study

Types of investigation methodologies

Controlled experiment, case study, classification & identification, correlation study, fieldwork, literature review, modelling & simulation, and product, process or system development

Allocation

Participants are divided between the experimental and control groups

Experimental group (in controlled experiment)

Exposed to the independent variable and receives the experimental treatment

Control group (in controlled experiment)

Forms a baseline level to compare with the experimental group

Random allocation

A method used that gives every member of the sample an equal opportunity of either being in the control or experimental group

Investigation designs

Between subjects design, within subjects design, mixed design

Between subjects design

When participants are randomly allocated to either the control or the experimental condition

Within subjects design

Involves all participants in the sample completing both the experimental and control conditions

Stratified sampling strengths and limitations

Strength: Representative of the population, improving external validity

Limitation: Difficult to obtain names of all members of the population

Random sampling strengths and limitations

Strength: Large samples are representative of the population, improving external validity

Limitation: Small samples may not be representative of population

Controlled experiment strengths and limitations

Strength: Can be repeated to test reliability of results

Limitation: Such strictly controlled conditions are difficult to maintain, so results can be affected by extraneous variables.

Between subjects design strengths and limitations

Strength: Most time-efficient

Limitation: Less control over the extraneous variables of participants, lowering validity

Within subjects design strengths and limitations

Strength: No varying extraneous variables of participants, improving validity

Limitation: More time consuming

Mixed design

Involves a combination of a between subjects design and a within subjects design

Mixed design strengths and limitations

Strength: Can test the effect of multiple independent variables

Limitation: Less control over participants’ prior knowledge

Case study

An investigation of a particular activity, behaviour, event or problem that contains a real or hypothetical situation and includes real-world complexities

Case study strengths and limitations

Strength: Used to study experiences where it would be unethical to conduct a controlled experiement

Limitation: One person / small group of people cannot be representative of a population, so low external validity

Classification and identification

A type of investigation that involves arranging phenomena, objects or events into a manageable sets, and recognising phenoma as beloning to a particular set.

Classification and identification strengths and limitations

Strength: Can help make predictions and inferences

Limitations: Can lead to stereotyping, prejudice or discrimination

Correlational study

Involve planned observation and recording of events and behaviours that have not been manipulated in order to understand the relationships existing between variables, identify which factors may be of greater importance and make predictions

Correlational study strengths and limitations

Strength: The direction and strength of a relationship between variables can be determined

Limitation: Correlation does not equal causation, so you cannot assume that one variable causes a change in the other

Fieldwork

Collecting information by observing and interacting with a selected environment

Fieldwork strengths and limitations

Strength: Natural settings are more likely to show behaviour that reflects real life

Limitation: Ethical concerns with the lack of informed consent in some cases

Literature review

Involves collating and analysing secondary data findings and/or viewpoints

Modelling and simulation

Involves constructing and/or manipulating a physical or conceptual model of a system

Product, process and system development

Involves the design of a product, a process or a system to meet a human need

Ethical concepts

Integrity, justice, non-maleficence, beneficence, respect

Integrity

The commitment to searching for knowledge and understanding, and the honest reporting of all sources of information and results

Justice

Involves the moral obligation to ensure that competing claims are considered fairly, that there is no unfair burden on a particular group from an action, and that there is fair distribution and access to the benefits of an action

Beneficence

The commitment to maximising benefits and minimising the risks and harms

Non-maleficence

To avoid causing harm

Respect

Involves considering the value of living things, giving due regard, and considering the capacity of living things to make their own decisions

Ethical guidelines

Confidentiality, voluntary participation, informed consent, withdrawal rights, use of deception, debriefing

Confidentiality

Ensuring that participants remain anonymous, and their personal information is kept private, protected and secure throughout the study

Voluntary participation

Ensures that each participant freely agrees to participate in a study, with no pressure or coercion

Informed consent procedures

Conducted before a study begins, where participants agree to participate in the research after they have received all the details of the investigation including the nature and purpose, methods of data collection and potential risks

Withdrawal rights

Ensure that participants are free to discontinue their involvement in a study without receiving a penalty

Debriefing

Conducted at the end of the study and is when participants are informed of the true aims, results and conclusions of the study

Deception

Involves withholding the true nature of the study from participants if their knowledge of the true purpose may affect their behaviour and the subsequent validity of the investigation

Primary data

Collected through first-hand experience for an intended purpose

Secondary data

Obtained second hand through research conducted or data collected by another person for another purpose. Secondary data may be used when it is not possible to collect primary data because of time or cost, or if participants are unavailable​

Qualitative data

Describes characteristics and qualities.

Quantitative data

Involves measurable values and quantities and can be compared on a numerical scale.

Percentage

Part of a whole, expressed as a proportion out of 100

Percentage change

A calculation of the degree of change in a value over time ​
- a positive percentage change indicates a percentage increase, a negative percentage change indicates a percentage decrease ​

Measures of central tendency

A category of statistics that describe the central value of a set of data - mean, median, mode

Mean

The average value of a set of data

( sum of all data points / no. of data points )

Median

The middle value in an ordered set of data

Mode

The value that occurs the most frequently within a set of data

Measures of variability

A category of statistics that describe the distribution of data

Standard deviation

Shows the spread of the data around the mean. It shows how close each data value lies to the average, or how far spread out they are – in other words, how much the values vary. ​

Ways of organising and presenting data

Charts & graphs (bar charts and line graphs), tables

True value

The value, or range of values, that would be found if the quantity could be measured perfectly

Accuracy

How close a measurement is to the true value of the quantity being measured

Precision

Refers to how close a set of measurement values are to each other. It describes how exact a measurement is, and how much a value agrees or is consistent within a set of values that were measured under the same conditions. ​

Repeatability

How close successive measurements of the same quantity are when carried out under the same conditions

Reproducibility

How close measurements of the same quantity are when carried out under different conditions

Reproducibility vs repeatability

• Repeatability refers to the extent to which a study's findings can be replicated or repeated under similar conditions, typically by the same research team. Repeatability assesses the consistency and stability of a study's results over time and with the same research procedures.​

• Reproducibility refers to the extent to which a study's findings can be independently obtained by other researchers using different methods, instruments, or settings. Reproducibility assesses the robustness and generalizability of a study's results across different contexts.​

Validity

Refers to whether a measurement measures what it is supposed to be measuring

Internal validity

Refers to a study investigating what it sets out or claims to investigate

External validity

Refers to whether the results of the research can be applied to similar individuals in a different setting

Personal errors

Include mistakes, miscalculations and observer errors made when conducting research. ​

Measurement errors

The difference between the measured value and the true value of what is being measured - systematic errors and random errors.​

Systemic errors

Affect the accuracy of a measurement by causing readings to differ from the true value by a consistent amount or by the same proportion each time a measurement is made.

Random errors

Affect the precision of a measurement by creating unpredictable variations in the measurement process; they result in a spread of readings.

Uncertainty

Refers to a lack of exact knowledge of the value being measured

Contradictory data

Incorrect data

Incomplete data

Missing data - questions without answers or variables without observations

Outliers

Values that lie a long way from other results