Topic guide · Learning, memory and education / Methods, evidence and reproducibility
How do teaching goals, tasks and feedback fit together?
Design one lesson whose intended outcome, practice task and assessment call for the same kind of thinking.
Topic guide · Perception, attention and action / Methods, evidence and reproducibility
How does attention shape what we notice?
Move from selection and perceptual tasks to competing accounts of attention, measurement and the separate question of awareness.
Topic guide · Evolution and other minds / Cells, circuits and brains / Methods, evidence and reproducibility
What can—and cannot—we learn by comparing brains across species?
Move from brain size and proportional scaling to cellular development and task-specific behaviour, without turning the comparison into a ranking of intelligence.
Topic guide · Mental health and intervention / Methods, evidence and reproducibility
How is evidence for depression treatment assessed?
Connect the clinical question, comparison, outcome and guideline judgement without choosing treatment for an individual.
Topic guide · Mental health and intervention / Methods, evidence and reproducibility
What can a psychiatric diagnosis explain—and what can it not?
Separate description, assessment, causal hypotheses and research dimensions.
Topic guide · Computational approaches and AI / Cells, circuits and brains / Methods, evidence and reproducibility
How can a model help explain neural activity?
Connect modelling goals, simplified neuronal mechanisms, spike data and fitting exercises, with an optional route into network models.
Topic guide · Consciousness and philosophy / Reasoning and decisions / Methods, evidence and reproducibility
Do brain recordings show that free will is an illusion?
Analyse the gap between an experimental task, a neural prediction and a philosophical conclusion about control.
Topic guide · Methods, evidence and reproducibility / Reasoning and decisions
When can a study support a causal explanation?
Separate an observed relationship from a specified intervention contrast and inspect the assumptions connecting them.
Topic guide · Methods, evidence and reproducibility
How do you turn a question into a testable experiment?
Connect a question, a measure, a comparison and an analysis before collecting observations.
Topic guide · Personality and individual differences / Development across life / Methods, evidence and reproducibility / Evolution and other minds
How do genes and environment influence behaviour?
Interpret family and twin comparisons, population heritability and developmental experiments without turning them into percentages of a person or claims of inevitable outcomes. This route explains foundational inference, not personal genetic risk or modern genome-wide prediction.
Topic guide · Social and cultural behaviour / Evolution and other minds / Methods, evidence and reproducibility
How do group identities shape collective behaviour?
Compare identity, norms, incentives and authority as possible explanations, then examine the move from research findings to policy proposals.
Topic guide · Cells, circuits and brains / Methods, evidence and reproducibility
How can we study what a human brain is doing?
Compare measurement approaches, experimental contrasts and interpretational limits before following a specialist brain-imaging or connectivity route.
Topic guide · Evolution and other minds / Consciousness and philosophy / Methods, evidence and reproducibility
How can we investigate consciousness in other animals?
Compare evidence about experience with evidence about particular behavioural abilities, while making alternative explanations explicit.
Topic guide · Personality and individual differences / Methods, evidence and reproducibility
How can personality be described without turning traits into types?
Describe traits as dimensions supported by observations, with context and change still visible.
Topic guide · Reasoning and decisions / Methods, evidence and reproducibility
How should we reason with uncertain information?
Build a probability model, condition on information and expose independence assumptions before comparing formal rules with human judgements.
Topic guide · Methods, evidence and reproducibility / Personality and individual differences
How can you tell whether a measure is reliable and valid?
Separate what a score records, how consistently it behaves and which interpretation the evidence supports.
Topic guide · Methods, evidence and reproducibility / Computational approaches and AI
How do transparent choices make a result more reproducible?
Connect explicit analysis decisions and readable computation with the separate tasks of reproducing a result and testing a claim again.
Topic guide · Emotion, motivation and sleep / Cells, circuits and brains / Methods, evidence and reproducibility
How are sleep and biological clocks studied?
Connect timing, light cues and experimental measurements while keeping sleep and circadian questions distinct.
Topic guide · Emotion, motivation and sleep / Mental health and intervention / Methods, evidence and reproducibility
How do researchers study stress and health?
Separate a stressor, a measured response and an outcome, then examine the study design linking them.
Topic guide · Consciousness and philosophy / Methods, evidence and reproducibility / Computational approaches and AI
How can competing theories of consciousness be tested?
Distinguish a named theory, a particular prediction, a measurement and the interpretation of a result.
Topic guide · Evolution and other minds / Social and cultural behaviour / Methods, evidence and reproducibility
How can evolutionary explanations of human behaviour be tested?
Separate mechanism, development, ancestry and possible function, then ask which comparative observations could distinguish rival accounts.
Topic guide · Methods, evidence and reproducibility
What can a confidence interval or hypothesis test tell you?
Connect sampling variation, test behaviour and interval estimates without turning them into probabilities that a scientific claim is true.
Topic guide · Personality and individual differences / Methods, evidence and reproducibility
What do intelligence test scores measure?
Distinguish a performance, a score, a construct and a causal explanation when reading intelligence claims.
Topic guide · Learning, memory and education / Methods, evidence and reproducibility
What can learning analytics actually tell an educator?
Connect recorded learning traces to a defensible educational question, distinguishing measurement, prediction and evidence of improvement.
Topic guide · Methods, evidence and reproducibility / Mental health and intervention
What makes a therapy trial informative?
Work through comparison, assignment, outcomes, masking and generalisation using an original study-design exercise.
Topic guide · Reasoning and decisions / Methods, evidence and reproducibility
When are choices biased, and what is the comparison standard?
Specify the information, goal and comparison rule before interpreting a response as a judgement bias.
Lectures and explanations
Selections below prioritise source-checked annotations. Inclusion does not assess scientific correctness.
University of Oxford Podcasts · Source-checked annotation
Moving beyond integration and differentiation in measures of neural dynamics
Pedro Mediano develops information-theoretic ways to distinguish redundancy and synergy when describing neural dynamics.
Open Yale Courses · Source-checked annotation
Lecture 3 - Biology, Nutrition and Health I: What We Eat
Examines ways of measuring food intake, differences between individual and population measures, and errors in reporting portions and nutrition.
MIT OpenCourseWare · Source-checked annotation
Lecture 4: Brain II
Compares lesion, stimulation and recording approaches to studying the human brain, with attention to what each kind of evidence can and cannot show.
MIT OpenCourseWare · Source-checked annotation
Lecture 3: Independence
Distinguishes independence of two events, independence of a collection and pairwise independence.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Hypothesis testing using confidence interval
Connects confidence intervals with one-sided and two-sided tests, including R output. The inspected examples compare proposed means or proportions with intervals rather than treating the p-value as the only useful result.
MIT OpenCourseWare · Source-checked annotation
11. Spectral Analysis Part 1
Introduces complex Fourier series, continuous and discrete transforms, and power spectra in a neural-computation course.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Motivation
Uses manufacturing examples to turn an informal claim into a statement about a population parameter, then introduces the sequence of a statistical test. The examples concern such quantities as a mean rather than a complete scientific explanation.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Hypothesis testing of means
Compares tests concerning means, including different treatments of known and unknown variability. The inspected worked material includes paired measurements and R plots, drawing attention to how observations are related.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Lecture 07 : Variables and Types of Data
Explains types of variables and data using examples such as clothing sizes and prices. The inspected passages also distinguish sources of data, including surveys and primary and secondary collection.
MIT OpenCourseWare · Source-checked annotation
9: Lateral Geniculate Nucleus (LGN) / Primary Visual Cortex (V1)
Connects retinal and cortical receptive fields with visual population codes. The inspected opening compares centre–surround and orientation-selective responses, then uses the tilt aftereffect to motivate a population-response hypothesis.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Lecture 06 : Objectives, Steps and Basic Definitions
Introduces the purpose of descriptive statistics, the distinction between a sample and a population, and numerical and graphical ways to summarise variation. The instructor explains that the course focuses on implementing these tools in R.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Lecture 08 : Absolute Frequency, Relative Frequency and Frequency Distribution
Builds absolute and relative frequency tables, moving from category counts to proportions. The checked R material shows how table and length operations implement the denominator used in the summary.
Open Yale Courses · Source-checked annotation
Lecture 20 - The Good Life: Happiness
Asks how treatment efficacy can be assessed, then turns to happiness, cultural variation and people's predictions about future satisfaction.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Lecture 10 : Bar Diagrams
Creates bar diagrams from frequency tables and relative frequencies. The inspected examples show how category counts, denominators, labels and graphical parameters affect the resulting display in R.
Open Yale Courses · Source-checked annotation
Lecture 10 - Mixed Strategies in Baseball, Dating and Paying Your Taxes
Distinguishes three interpretations of mixed strategies: actual randomisation, uncertainty about a player and proportions of a population using different actions.
NPTEL — National Programme on Technology Enhanced Learning · Source-checked annotation
Lecture 18 : Range, Interquartile Range and Quartile Deviation
Shows why distributions with a similar centre can have different spreads. The inspected examples calculate the range and interquartile range in R and discuss how these summaries use different parts of the observations.