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---
title: "Measures"
format:
html: default
revealjs:
output-file: measures-slides.html
pdf:
output-file: measures-handout.pdf
docx:
output-file: measures.docx
---
{{< include mds/_measures.qmd >}}
## Further reading {#sec-further-reading}
- @billingsley1995probability
develops measure theory and builds probability on it.
Its early chapters define $\sigma$-algebras, measures, and their basic properties.
- @folland1999real
is a graduate text on measure and integration;
its first chapters treat $\sigma$-algebras and measures.
- @gut2013
is a graduate course in probability
that opens with a chapter on introductory measure theory.
- @wikipedia_sigma_algebra --- $\sigma$-algebras and their generators
- @wikipedia_closure_mathematics --- closure under an operation
- @wikipedia_borel_set --- Borel sets
- @wikipedia_disjoint_sets --- disjoint sets
- @wikipedia_series_mathematics --- series and partial sums
- @wikipedia_monotone_convergence_theorem --- the monotone convergence theorem
- @wikipedia_sigma_additive_set_function --- additive and $\sigma$-additive set functions
- @wikipedia_measure_mathematics --- measures, with examples
- @wikipedia_counting_measure --- counting measure
- @wikipedia_measurable_space --- measurable spaces
- @wikipedia_lebesgue_measure --- Lebesgue measure and its construction
- @wikipedia_null_set --- null sets
- @wikipedia_almost_everywhere --- properties that hold almost everywhere
- @wikipedia_finite_measure --- finite measures
- @wikipedia_sigma_finite_measure --- $\sigma$-finite measures
- @wikipedia_probability_measure --- probability measures
- @wikipedia_probability_space --- probability spaces
- @wikipedia_sample_space --- sample spaces
- @wikipedia_event_probability_theory --- events
- @wikipedia_outcome_probability --- outcomes
- @wikipedia_measurable_function --- measurable functions
- @wikipedia_lebesgue_integration --- the Lebesgue integral
## References {.unnumbered}
::: {#refs}
:::