Introduction to Psychology and Scientific Inquiry

Secondary

How psychology became a science — and how psychologists know what they know.

This collection covers the foundations of psychology as a science, including its definition, goals, historical schools of thought, modern perspectives, research methods, ethical considerations, and research design principles. Aligned with the IPsyO (International Psychology Olympiad) syllabus.

Academic primerResearch methods

Earn2CreditsinPsychology

3Modules14Sessions172Cards66Quizzes

Modules in this Collection’s System

Hover a module to read it directly

1. Overview of Psychology

What psychology is, who built it, and the seven lenses modern psychologists use to read a behavior.

4Sessions

2. Scientific Inquiry and Research Methods

From hypothesis to replication — the scientific method as it actually runs inside a psychology lab.

4Sessions

3. Research Design

Designing studies that can answer the question you're asking — variables, groups, validity, sampling, and ethics.

6Sessions

What You'll Walk Away With

1seven-perspectives cheat sheet for reading any psych study through psychodynamic, behavioral, cognitive, humanistic, biological, evolutionary, and sociocultural lenses
1research-method decision tree to pick descriptive vs. correlational vs. experimental designs by the question being asked
1correlation-causation trap card listing the three alternative explanations to rule out before any causal claim
1validity / reliability matrix separating internal vs. external validity and test-retest vs. inter-rater vs. internal-consistency reliability
1ethics pre-flight checklist covering informed consent, deception rules, debriefing duties, and IRB review triggers

You'll Have Answers To

?What makes psychology a *science* rather than just a collection of opinions about human nature?
?Why is the year 1879 conventionally called the birthday of psychology — and what exactly happened that year?
?If correlation doesn't prove causation, what does — and why are experiments the only design that qualifies?
?How do psychologists decide a study is ethical *before* the data are collected, not after?
?When a study reports p < .05, what does that actually mean — and why isn't it the same as 'the finding is important'?

Critical Concepts Explored

Empiricism and operationalizationThe four goals: describe, explain, predict, changeStructuralism vs. functionalismThe seven modern perspectivesIndependent vs. dependent variableRandom assignment and control groupsCorrelation coefficient and its three rival explanationsInternal vs. external validityStatistical significance vs. effect sizeIRB review and informed consent

Editor's Note

“A disciplined on-ramp into psychology as a science”

This collection does the unglamorous work most intro texts skim: teaching readers to tell descriptive research from correlational from experimental, to smell a confound at ten paces, and to read effect size alongside p-values. Tight, well-sourced, and genuinely Olympiad-grade — not a pop-psych greatest-hits reel.

Editor's Brief

Who it's for: Students preparing for the International Psychology Olympiad, AP Psychology, or any first-semester university intro psychology course — plus self-learners who want a defensible mental model of how psychological knowledge is actually produced.
What stands out: Every claim is traced back to a specific research method and its limits; the collection treats methodology as content, not prelude, so readers leave able to evaluate a study, not just recite findings.
Read if: You want to understand not only what psychology says but how it earns the right to say it — and you're allergic to hand-wavy summaries that skip the epistemics.

Gold Quotes

Every correlational finding has three alternative explanations: reverse causation, a third variable, or chance. Saying 'X causes Y' from a correlation is the single most common violation of psychological reasoning.

The collection makes this the spine of its research-methods unit. Correlation measures association; only a true experiment — with manipulation of the IV, random assignment, and a control group — can license a causal claim. Students who internalize this cheat-sheet stop falling for the 'breakfast boosts grades' headline class of errors.

A measure can be reliable without being valid. Consistency is not the same as accuracy.

A broken thermometer that always reads 72°F is perfectly reliable and entirely invalid. The distinction separates internal validity (did the IV cause the DV?) from external validity (does the result generalize?) and from the construct-validity question (are we even measuring the right thing?). Reliability is a necessary but insufficient condition for a good measure.

Statistical significance tells you a result is unlikely by chance. Effect size tells you whether it matters.

A p-value under .05 can be produced by a trivial effect if the sample is large enough. Cohen's d and r² — not p-values — answer the question a clinician or policymaker actually cares about: how big is the thing? Serious psychology reports both together; headlines report only the p-value.

About the Curator

IInternational Psychology Olympiad

International Psychology Olympiad is the editorial voice behind LearningFirst's IPsyO-aligned collections — producing rigorous, exam-ready primers on core psychological science for learners preparing for competitions and introductory university coursework.