The Science of Everything Podcast

A discussion of the shape of the Earth and the difficulties and conventions involved in describing a three-dimensional surface on a two-dimensional map, including an overview of some of the major map projections and their various limitations. This leads in to an overview of Earth's axial tilt and variation in solar insolation by latitude as an explanation for the seasonal variation in weather across the planet. Recommended pre-listening is Episode 87: The Geography of Planet Earth.

An overview of some of the key geographic features of planet Earth, including a discussion of the concept and classification of continents, the major mountain ranges and major river basins around the planet. I also discuss the major world biomes, their major climactic and botanical features, and their relative locations across the Earth.

An outline of the various lines of evidence in favour of the theory of evolution by natural selection, including a discussion of natural and artificial examples of natural selection in action, as well as a review of the evidence from the fossil record, comparative anatomy, biogeography, and molecular evidence. Recommended pre-listening is Episode 21: Introduction to Evolution.

A discussion of some of the major conceptual aspects of Quantum Field Theory, including the concept of a quantum field, classical field theory, harmonic oscillators, second quantisation, interacting theories, and the relationship of QFT to other branches of physics. Recommended pre-listening is Episodes 83 and 84, Advanced Quantum Mechanics parts I and II.

Continuing on from the previous episode, here I discuss some more advanced topics in Quantum Mechanics, including Noether’s theorem, the particle statistics of Bosons and Fermions, perturbation theory, and the EPR paradox. Recommended Pre-listening is Episode 83: Advanced Quantum Mechanics Part I.

An examination of some more advanced concepts of quantum mechanics, focusing on describing Dirac's bra-ket formulation of quantum theory. I discuss the formulation of quantum mechanics in terms of vectors in Hilbert spaces, Hermitian operators as corresponding to observables, orthogonality of eigenstates, incompatible observables, and Schrodinger's equation. Recommeded pre-listening is Episode 14: Principles of Quantum Mechanics.

A discussion of the evidence and methodological issues pertaining to explaining the causes of racial differences in intelligence, with a focus on evaluating the hereditarian hypothesis that such differences are largely genetic. Recommended pre-listening is Episode 81: Intelligence Part 2.

Continuing the series on intelligence, in this episode I discuss the genetic and neurological correlated of intelligences, the efficacy of measures to increase intelligence, and the causes and consequences of the Flynn effect. Also includes an analysis of the heritability of intelligence and how to properly interpret heritabilty research. Recommended pre-listening is Episode 80: Intelligence Part 1.

The first in a three part series on human intelligence, covering debates about the definition of intelligence, how intelligence is measured, factor analysis and the origin of the g factor, and interpretations of the g factor as corresponding to intelligence. Also includes an analysis of Gardner's theory of multiple intelligences, and the cross-cultural validity of intelligence tests. Recommended pre-listening is Episode 79: Basic Concepts in Statistics. If you enjoyed the podcast please consider supporting the show by making a paypal donation or becoming a patreon supporter. https://www.patreon.com/jamesfodor https://www.paypal.me/ScienceofEverything

A concise introduction to key concepts of statistics, explained in as clear a manner as possible. Includes a discussion of key concepts of probability, types of statistical data, sampling methods, the difference between descriptive and inferential statistics, statistical significance, and p-values. I conclude with a brief look at three common statistical tests; the chi-square test, t-test, and linear regression.