Year 12 ATAR Psychology (Broken!)

So sorry, I accidentally deleted half of the flashcards on this set :( I'll fix it when exams roll around.

The 3 R’s in Animal Ethics (In Order)

Replacement, Reduction, Refinement

Animal Ethics: Replacement

The development of a method which does not require the use of animals.

Animal Ethics: Reduction

Keeping the amount of animals in a study to the minimum amount necessary required to achieve the proposed aim / satisfy good experimental design.

Animal Ethics: Refinement

Improving the techniques and method of the study to minimise potential harm in animal subjects.

All 7 Ethical Requirements

1. Protection from physical / psychological harm

2. Informed consent

3. Withdrawal rights

4. Limited deception with debreifing

5. Confidentiality post-research

6. Privacy during research

7. Voluntary participation

Ethical Guidelines: Protection from Harm

Psychologists take steps to avoid harming their participants when avoidable and to minimise it as much as possible when unavoidable.

Ethical Guidelines: Informed Consent

A participant must provide written consent in order to partake in a study after being provided with potential risks and benefits, as well as their participant rights in the study. Information about the procedure should also be given if it will not impact the outcome of the study.

Ethical Guidelines: Withdrawal Rights

The right of the participant to cease their participation in a study at any point, whether before, during, or after, without any consequences or pressure to continue.

Ethical Guidelines: Deception

Psychologists must not intentionally mislead participants in regards to the study unless the results would be confounded if the participants had much information before taking part in the study. Debriefing is required when deception is used.

Process of Debriefing

The element of deception must be described, reasons for the deception must be given, participants must be given the opportunity to ask questions and withdraw their data, and in case of potential harm the researchers must provide participants with avenues for counselling.

Ethical Guidelines: Confidentiality

The obligation of the researcher not to disclose or use private information of participants for any reasons aside from why it was given to them.

Ethical Guidelines: Privacy

The obligation of the researcher to collect only the information which is relevant to the study from participants.

Ethical Guidelines: Voluntary Participation

Participants must not be coerced / pressured into partaking in a study. There must also be no consequences for lack of participation.

Role of Ethics Committees

An Ethics Committee controls funding to experiments and ensures that ethical guidelines are adhered to before and during the conduct of a study.

Convenience sampling

Gathering a sample group of people that are readily available to the experimenter.

1 Strength and 1 Weakness of Convenience Sampling

• Easy and cheap to set up

• Can cause bias and create an unrepresentative sample

Random sampling

Equal chance of every available member of the population being selected for the sample group

1 Strength and 1 Weakness of Random Sampling

• Ensures a highly representative sample without any potential for bias

• Can be logistically challenging and not all members of the sample will agree to participate / continue to participate

Stratified sampling

People are broken into groups based off of relevant characteristics (i.e. age) and then an equal amount of people from each group is selected.

1 Strength and 1 Weakness of Stratified Sampling

• Ensures the sample is very representative

• Is logistically challenging and time consuming to set up

Snowball Sampling

Participants recruit more participants and those participants recruit even more.

1 Strength and 1 Weakness of Snowball Sampling

• Useful when the population is very small and difficult to contact

• May involve bias and not be representative of the entire population

Experimental Design: Independent-Groups

Refers to the random allocation of members of the sample group to the control or experimental group. Is cost and time effective, but due to its random nature there is a chance that there could be differences between the members of both groups (an extraneous variable).

Experimental Design: Matched-Participants

Participants are paired with one another based off of shared characteristics, with each member of the pair being assigned randomly to the control or experimental group. This helps to elimenate differences between participants as an extraneous variable, however it is quite cost and time inefficient seeing as a pre-test needs to occur to gague the participants abilities before matching them. Also, if a participant drops out, their pair also needs to be removed.

Experimental Design: Repeated-Measures

A single group is exposed to both the control and experimental conditions. This completely eliminates differences between participants as an extraneous variable and is time effective, however it can lead to the ‘order effect’. This refers to how results might change due to the sequence of the controlled and experimental tests - after completing the same test twice, motivation might decrease or skill might increase which could skew the results.

Research Design: Experimental

An experiment which employs a systematic / scientific process to test the impact of the independent variable on the dependent variable. Involves a high degree of control over extraneous variables.

Research Design: Non-Experimental

Research where the variable for the investiagation is unable to be manipulated but may be measured.

Research Design: Observational

Behaviour is systematically recorded and observed in a real life / natural setting. Difficult to remove extraneous variables.

Research Design: Case Study

An in depth investigation of a single individual, event, community, etc. Limited participants, so hard to generalise, but can be very useful for incredibly small populations.

Research Design: Correlational

Observing the strength in relationships between variables. Measurable, but not manipulatable. Correlation does not equal causation, making this less reliable.

Research Design: Longitudinal

Studying the changes seen in the sample over time, participants usually being surveyed once a year. Suffers from being time-consuming, expensive, and having guaranteed dropouts. Very representative data.

Research Design: Cross-Sectional

Cross-sectional studies are once-off studies in which people of differing areas of a population are all experimented on at once.

Reliability

The consistency of a test - does a test produce the same / similar results every time? Tests with low sample sizes are less reliable.

Tests must be reliable across…

• Time (test-retest reliability)

• Materials (internal consistency)

• Researchers (interrater reliability)

Validity

The degree to which a test or measure adequately addresses the research question and what it intends to measure

Qualitative data

Any form of open-ended question that measures non-numerical data or data that cannot be mapped to a numerical value.

Quantitative data

Data that is numerical and can be plotted onto a graph or table

Subjective data

Anecdotal information that comes from opinions, perceptions, or experiences. For example, a description of symptoms or pain level.

Objective data

Information that is considered factual and unable to be disputed regardless of the person interpreting or presenting it.

Independent Variable

The variable which is manipulated

Dependent Variable

The variable which is measured as a result of manipulations to the independent variable

Control Variable

A variable which stays unchanging in the study as it could influence results

Confounding variable

Types of extraneous variables which influence both the dependent and independent variable, distorting the relationship between both.

Extraneous Variables

Any uncontrolled variable within an experiment that is not being studied which has the potential to influence the dependent variable

Participant-related extraneous variables + example

Extraneous variables that appear as a result of the participant and any potential differences they may have to other participants. Perhaps they are more skilled at the task or had more training.

Researcher-related extraneous variables

Extraneous variables that develop as a result of the potential biasses of the researcher. These can also include demand characteristics and the experimenter effect. For example, maybe the researcher has racial biasses and marks a POC participant more harshly, skewing the results.

Environment-related extraneous variables

Environment extraneous variables are variables related to the environment that skew the results of the test. Maybe the environment is too noisy, distracting participants.

Subjective Data: 3 Examples

Pain level, levels of happiness, opinions towards subjects

Objective Measures: 3 Examples

Heart rate, galvanic skin response (GSR - measuring the change in electrical current in the skin to test stress or arousal), breath rate

Subjective Measures: 3 Examples

Checklists and rating scales, including likert scales

Experimenter Effect

The potential bias in the experimenter to interpret data or influence participants to come to the conclusion they desire.

Demand Characteristics

Where participants subconsciously form an assumpton of the experimenters aim based off of the experimenter effect and change their behaviours

Random Allocation of Participants

Randomly allocates certain participants to either the control or the experimental group of a study to reduce risk of researcher bias

Single-Blind Procedures

When the participant is unaware of the group they are in, but the experimenter is. Limits likelihood of demand characteristics.

Standardisation of Procedures

The procedures participants undertake must be identical to ensure data is valid and reliable.

Scatterplot

• Used to depict data from a correlational study

• Shows the values of two different variables on each axis

• If the value increases along both the X and Y axes, it is a positive correlation

• The level of clustering in the dots corresponds to how strong the relationship is

Bar / Collumn Chart (Description, Axes)

• Made up of a series of bars that do not touch

• They show categorical data - the difference in a particular value between various different categories

• The bars don’t touch to show that the data is NOT continuous

• Sometimes bar charts can represent two different cats within one bar (e.g. male vs female performance in a single category). In this case values are stacked atop one another and colour coded

Line Graph (Description, Axes)

• Depicts how one variable continuously changes (e.g. temp) as another changes (e.g. time)

• In an experiment, the IV is plotted on the x / horizontal axis, and the DV is plotted on the y axis

• The variable on the x axis needs to be continuous (progressively increasing)

Histogram (Description, Axes, Example)

• A graph which plots the frequency of a numeric variable

• The y axis depicts frequency, and the x axis depicts the numeric variable

• Histograms are represented with bars without gaps between them

• The data cannot be categorical - must be continuous and numerical, sometimes grouped into classes / bins (i.e. age ranges 1-10, 11-20)

Frequency Table

Used to show the frequency of a specific data point. One collumn for the categories and one collumn for the frequency of that category.

Pearson’s Correlation Coefficient

A numerical value between 1 and -1 which measures the direction and strength of the relationship between two variables.

Pearson’s Correlation Coefficient: Meaning of Values

The closer to 1 / -1, the stronger the correlation. The closer to 0, the weaker the correlation.

• 1: Very strong positive correlation

• 0 - 1: Positive correlation

• 0: No correlation

• 0 - -1 Negative correlation

• -1: Very srong negative correlation

Directional Hypothesis + Mark Division

A hypothesis in which the relationship between two variables can be predicted directionally (e.g. people with caffeine will score higher)

• State sample / populatioin

• State direction

• IV

• DV

Non-Directional Hypothesis + Mark Division

A hypothesis in which the relationship between two variables can be predicted, but a direction is not given (e.g. caffeine will have an impact on score - not specifying whether it will be pos. or neg.)

• Sample / population

• Difference or no difference

• IV

• DV

Inquiry Question

A question which aims to explore an aspect of a psychological topic without making claims or assumptions. Answered by the hypothesis.