A first course in causal inference:
"The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught ov...
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Boca Raton, FL
CRC Press
2024
|
Ausgabe: | First edition |
Schriftenreihe: | Chapman & Hall/CRC texts in statistical science
|
Schlagworte: | |
Zusammenfassung: | "The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught over the past seven years, only requires basic knowledge of probability theory, statistical inference, and linear and logistic regressions. It assumes minimal knowledge of causal inference, and reviews basic probability and statistics in the appendix. It covers causal inference from a statistical perspective and includes examples and applications from biostatistics and econometrics. It would be suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments"-- |
Beschreibung: | 2406 |
Beschreibung: | xxvi, 421 Seiten |
ISBN: | 9781032758626 1032758627 9781032776316 1032776315 |
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520 | 3 | |a "The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught over the past seven years, only requires basic knowledge of probability theory, statistical inference, and linear and logistic regressions. It assumes minimal knowledge of causal inference, and reviews basic probability and statistics in the appendix. It covers causal inference from a statistical perspective and includes examples and applications from biostatistics and econometrics. It would be suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments"-- | |
653 | 0 | |a Mathematical statistics / Textbooks | |
653 | 0 | |a Probabilities / Textbooks | |
653 | 0 | |a Causation / Mathematical models | |
653 | 0 | |a Inference / Mathematical models | |
653 | 0 | |a Inférence (Logique) / Modèles mathématiques | |
776 | 0 | 8 | |i Online version |a Ding, Peng (Statistician) |t First course in causal inference |b First edition |d Boca Raton, FL : CRC Press, 2024 |z 9781003484080 |
943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-035075011 |
Datensatz im Suchindex
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adam_text | |
any_adam_object | |
author | Ding, Peng |
author_facet | Ding, Peng |
author_role | aut |
author_sort | Ding, Peng |
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building | Verbundindex |
bvnumber | BV049732837 |
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ctrlnum | (OCoLC)1432551011 (DE-599)BVBBV049732837 |
discipline | Mathematik |
edition | First edition |
format | Book |
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id | DE-604.BV049732837 |
illustrated | Not Illustrated |
indexdate | 2024-08-06T00:27:14Z |
institution | BVB |
isbn | 9781032758626 1032758627 9781032776316 1032776315 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035075011 |
oclc_num | 1432551011 |
open_access_boolean | |
owner | DE-188 |
owner_facet | DE-188 |
physical | xxvi, 421 Seiten |
publishDate | 2024 |
publishDateSearch | 2024 |
publishDateSort | 2024 |
publisher | CRC Press |
record_format | marc |
series2 | Chapman & Hall/CRC texts in statistical science |
spelling | Ding, Peng Verfasser aut A first course in causal inference Peng Ding First edition Boca Raton, FL CRC Press 2024 xxvi, 421 Seiten txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC texts in statistical science 2406 "The past decade has witnessed an explosion of interest in research and education in causal inference, due to its wide applications in biomedical research, social sciences, artificial intelligence etc. This textbook, based on the author's course on causal inference at UC Berkeley taught over the past seven years, only requires basic knowledge of probability theory, statistical inference, and linear and logistic regressions. It assumes minimal knowledge of causal inference, and reviews basic probability and statistics in the appendix. It covers causal inference from a statistical perspective and includes examples and applications from biostatistics and econometrics. It would be suitable for an advanced undergraduate or graduate-level course on causal inference, or postgraduate and PhD-level course in statistics and biostatistics departments"-- Mathematical statistics / Textbooks Probabilities / Textbooks Causation / Mathematical models Inference / Mathematical models Inférence (Logique) / Modèles mathématiques Online version Ding, Peng (Statistician) First course in causal inference First edition Boca Raton, FL : CRC Press, 2024 9781003484080 |
spellingShingle | Ding, Peng A first course in causal inference |
title | A first course in causal inference |
title_auth | A first course in causal inference |
title_exact_search | A first course in causal inference |
title_full | A first course in causal inference Peng Ding |
title_fullStr | A first course in causal inference Peng Ding |
title_full_unstemmed | A first course in causal inference Peng Ding |
title_short | A first course in causal inference |
title_sort | a first course in causal inference |
work_keys_str_mv | AT dingpeng afirstcourseincausalinference |