Key Science Skills

research question structure & example

"What is the effect of [Independent Variable] on the [Dependent Variable] in [Population]?"

example: "What is the effect of daily probiotic yogurt consumption on self-reported anxiety levels in adults aged 18–30?"

Aim structure & example

"To investigate the effect of [IV] on [DV] in [Population]."

The aim of this investigation is to explore the relationship between partial sleep deprivation and low mood in young people aged 18-25.

Hypothesis structure and example

"It is hypothesised that [Population] who [IV - Group 1] will [Direction] in [DV] compared to [Population] who [IV - Group 2/Control]."

IPAD

• Independent variable and dependent variables

• Population

• and

• Direction

It was hypothesised that Australian females aged 12–16 who experienced partial sleep

deprivation would be more likely to also experience low mood than those who did not

experience partial sleep deprivation.

Independent variable

The variable that is manipulated, changed, or controlled by the researcher.

• It is assumed to have a direct effect on the dependent variable.

Dependent Variable

• The variable that the researcher measures.

• It is observed to see how it changes in response to the IV.

Extraneous variable

any variable that is not the independent variable but may cause an unwanted effect on the dependent variable

controlled variables

variables other than the IV that a researcher holds constant in an investigation, to ensure that changes in the DV are solely due to changes in the IV

Controlled Experiment

Definition: A type of investigation used to test a causal relationship between an IV and DV in a controlled environment

Strengths:

• Infer Causality: Allows researchers to conclude that the IV directly caused the change in the DV

Limitations:

• conducted in a lab or highly controlled setting can mean it doesn't reflect "real life."

• This may cause participants to act unnaturally

Between-Subjects Design

Different participants are randomly allocated to either the control or experimental group

• Strength: No order effects (participants only do one condition).

• Limitation: Requires more participants; participant differences (e.g., intelligence) can affect results

Within-Subjects Design

Each participant is in both the control and experimental groups.

• Strength: Eliminates participant-related variables (everyone acts as their own control); requires fewer people.

• Limitation: Prone to order effects (boredom or practice).

Mixed Design

Combines elements of both within and between-subjects designs (e.g., testing two different groups over time).

• Strength: Allows researchers to see both differences between groups and changes over time.

• Limitation: Can be complex and costly to implement.

Case Study

An in-depth investigation of an individual, group, or event.

• Strength: Provides rich, highly detailed data; useful for rare phenomena (e.g., brain injuries).

• Limitation: Results cannot be generalised to the wider population

Correlational Study

Observes the relationship between two variables without manipulating them

• Strength: Can be used when experiments are unethical; identifies trends and relationships.

• Limitation: Correlation does not equal causation (you don't know which variable caused the change)

Fieldwork

Gathering primary data in a "natural" setting (e.g., observing students in a playground).

• Strength: High ecological validity (behaviour is natural).

• Limitation: Difficult to control extraneous variables; can be time-consuming.

Literature Review

Collating and analysing secondary data from existing research.

• Strength: Provides background for new research

• Limitation: can be time-consuming to find relevant sources.

Modelling & Simulation

Creating physical or conceptual representations to simplify or predict reality.

• Strength: Allows for testing of "what-if" scenarios safely.

• Limitation: A model or simulation is only a "representation"—it can never fully capture the infinite complexity of real-world human variables.

Product, Process, or System Development

Designing something to meet a human need (e.g., a new mental health app).

• Strength: Directly applies psychological theory to solve real-world problems.

• Limitation: This methodology is designed to solve a problem, not necessarily to test a broad psychological theory or establish cause-and-effect.

Population vs. Sample

• Population: The entire group of interest from which the sample is drawn (e.g., all VCE students).

• Sample: A smaller subset or group that is actually chosen from the population to participate in the study.

What makes a sample Representative versus Biased?

• Representative Sample: A sample that accurately reflects the relevant characteristics of the population (e.g., same ratio of ages/genders).

• Biased Sample: A sample that does not adequately represent the population (e.g., only testing girls when the population is all students).

Convenience Sampling

Definition: Selecting participants based on their availability and readiness to participate (e.g., the first 20 people you see in the library).

• Strength: Quick, easy, and inexpensive to perform.

• Limitation: Highly likely to produce a biased sample; results cannot be easily generalised

Random Sampling

Definition: Every member of the population has an equal chance of being selected (e.g., pulling names out of a hat).

• Strength: Reduces bias; the sample is more likely to be representative than convenience sampling.

• Limitation: Can be time-consuming to obtain a full list of the population; may still accidentally miss small sub-groups by chance.

Stratified Sampling

Definition: Dividing the population into distinct sub-groups (strata) based on shared characteristics, then selecting a sample from each stratum in the same proportion as they exist in the population.

• Strength: The most representative method; ensures all sub-groups are accurately represented.

• Limitation: Very time-consuming and expensive to identify and calculate sub-groups.

Differentiate between Sampling and Allocation.

• Sampling: The process of choosing people from the population to be in the study. (Population →Sample).

• Allocation: The process of assigning the chosen participants into groups within the experiment (e.g., Experimental group vs. Control group)

Random Allocation

Assigning participants to groups so that each person has an equal chance of being in the experimental or control group

Experimental Group

Exposed to the Independent Variable (the "treatment" or "intervention").

Control Group

Not exposed to the IV; provides a baseline to compare the experimental results against

Identification Example: In a study on caffeine and memory:

• Experimental: Group drinking 2 cups of coffee (IV).

• Control: Group drinking plain water (No IV).

Extraneous Variable

Any variable other than the IV that may cause an unwanted effect on the DV.

They should be controlled or monitored.

Confounding Variable

A variable other than the IV that has directly and systematically affected the DV.

• Crucial Rule: Confounding variables can only be identified at the end of an experiment after the results have been analysed.

Participant Variables

• Personal characteristics of the participants (e.g., age, intelligence, prior experience, mood).

• Example: In a memory test, one participant naturally has a better memory than another.

Situational Variables

• Factors in the environment that can affect the results (e.g., background noise, temperature, time of day).

• Example: One group takes a test in a quiet room while the other deals with a loud construction site outside.

Systematic Errors

Errors that differ from the true value by a consistent/predictable amount (e.g., a scale always being 100g light).

• Affects: Accuracy (how close the result is to the "true" value).

Random Errors

Unsystematic errors that occur due to chance and vary unpredictably (e.g., a participant being momentarily distracted).

• Affects: Precision (how consistent the measurements are with each other).

How can extraneous variables be reduced, prevented, or accounted for?

• Random Allocation: Spreads participant variables evenly across groups.

• Single-Blind Procedure: Participants don't know which group they are in (prevents Placebo Effect).

• Double-Blind Procedure: Neither participants nor researchers know who is in which group

Uncertainty

The lack of exact knowledge of the "true" value of the quantity being measured. All data has some uncertainty due to errors.

Outliers

Data points that differ significantly from other observations in the same sample.

• Impact: Outliers can distort the mean (average) and increase uncertainty.

Repeatability

the closeness of results when the same researcher repeats the experiment under the same conditions.

Reproducibility

the closeness of results when different researchers conduct the experiment using different equipment or settings to test the same hypothesis.

Internal Validity

Does the study actually measure what it claims to measure? (i.e., was the change in the DV only caused by the IV?).

External Validity

Can the results be generalised to the wider population or other settings?

Robust

Data is considered robust when it remains valid and reliable despite small changes in the conditions or errors.

Improvements to reduce uncertainty in data and avoid errors

• Increase Sample Size

• Standardise Procedures

• Refine Measurement Tools

Informed consent

• Participants should be informed of the nature, purpose and risks involved with a study prior to giving their consent to participate

• If under 18, consent must be given by a legal guardian

• Consent is usually provided in writing.

Beneficence

The consideration of the benefits or gains from research in relation to the risks (MAXIMISE benefits and MINIMISE risks/harm)

Non-maleficence (also known as the no-harm principle)

the idea that any potential harm should be avoided and minimised as much as possible

Integrity

the commitment to search for knowledge, and then honestly report information and findings.

Justice

The distribution of fair access to the benefits of research to everyone, ensuring that there is no burden on one group, and ensuring that any opposing claims are considered.

Respect

the belief that everyone has value in regards to their welfare and beliefs, and has a right to make their own decisions.

Withdrawal rights

Participants have the right to withdraw from a study at any time, and/or may also elect to have their results withdrawn from a study.

Voluntary participation

Participants must not be coerced or forced into participating, and must do so freely. There must not be adverse consequences for choosing not to participate.

Confidentiality

Participants names or identifying details must not be revealed.

*Deception

When the true nature or purpose of a study is not revealed to participants, it must be because doing so would undermine the results

*Note - If deception is used, debriefing MUST occur to explain the true nature/purpose of the study, and why the deception was necessary.

Debriefing

• The participants should be told of the results of a study after its completion

• They may also be offered counselling (depending on the nature of the study) and be allowed to have their results removed.