AICE Psychology Paper 2: Comprehensive Review

1. Sampling Methods

Understanding different sampling techniques is crucial for designing valid studies:

• Simple Random Sampling: Every individual has an equal chance of selection.​

• Stratified Sampling: The population is divided into strata, and random samples are taken from each stratum.​

• Cluster Sampling: The population is divided into clusters, some clusters are randomly selected, and all individuals within chosen clusters are sampled.​

• Systematic Sampling: Every nth individual is selected from a list of the population.​

• Convenience Sampling: Samples are taken from a group that is easy to access, which can introduce bias.​

• Voluntary Response Sampling: Individuals choose to participate, often leading to biased results due to strong opinions.​

2. Experimental Design Principles

Key principles ensure the reliability and validity of experimental research:

• Control: Keeping other variables constant to isolate the effect of the treatment.​

• Randomization: Randomly assigning subjects to treatment groups to reduce bias.​

• Replication: Repeating the experiment on many subjects to ensure reliability.​

• Blocking: Grouping subjects with similar characteristics and randomly assigning treatments within these blocks.​

3. Types of Studies

Different study types serve various research purposes:

• Observational Study: Observes individuals without manipulating variables. Cannot establish causation.​

• Experiment: Applies treatments to subjects and observes effects. Can establish causation.​

4. Experimental Terminology

Familiarity with these terms is essential:

• Subjects/Experimental Units: Individuals participating in the study.​

• Factors: Explanatory variables manipulated in the experiment.​

• Levels: Different values of the factors.​

• Treatments: Combinations of factor levels applied to subjects.​

• Placebo: An inactive treatment used to control for psychological effects.​

• Blinding: Keeping subjects or experimenters unaware of treatment assignments to prevent bias.​

• Double-Blind: Both subjects and experimenters are unaware of treatment assignments.​

5. Validity and Reliability

Assessing the quality of research involves understanding:

• Internal Validity: The extent to which the experiment measures what it intends to, without confounding variables.​

• External Validity: The extent to which results can be generalized to other settings or populations.​

• Reliability: The consistency of a measure; a reliable study yields similar results under consistent conditions.​

• Ecological Validity: The extent to which findings can be generalized to real-life settings.​

• Mundane Realism: How closely the experimental tasks mirror real-world activities.​Helpful Professor+4Reddit+4Quizlet+4

6. Data Types and Measures

Understanding data types aids in appropriate analysis:

• Quantitative Data: Numerical data that can be measured and analyzed statistically.​

• Qualitative Data: Descriptive data that provides insights into participants' thoughts and behaviors.​

• Measures of Central Tendency: Mean, median, and mode are used to summarize data.​

• Measures of Dispersion: Range and standard deviation indicate data variability.​

7. Hypotheses

Formulating clear hypotheses is fundamental:

• Directional (One-Tailed) Hypothesis: Predicts the direction of the expected effect.​

• Non-Directional (Two-Tailed) Hypothesis: Predicts an effect without specifying the direction.​

• Null Hypothesis: States there is no effect or difference; used as a baseline for statistical testing