🕷️ Crawler Inspector

URL Lookup

Direct Parameter Lookup

Raw Queries and Responses

1. Shard Calculation

Query:

Response:

Calculated Shard: 12 (from laksa174)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa012.int.ahrefs:8124/' \
  -H 'Content-Type: text/plain' \
  -H 'X-ClickHouse-Database: crawler3' \
  -H 'Authorization: Basic YXBpOg==' \
  -d 'SELECT getAhrefsURLFromUnparsed(src_unparsed) AS found_url, ifNull(toUnixTimestamp(download_stamp), 0) AS crawl_time, ifNull(toUnixTimestamp(props_url_first_seen), 0) AS first_indexed_time, download_http_code AS http_code, src_unparsed AS src_unparsed, src_root_hash AS src_root_hash, history_drop_reason AS history_drop_reason, meta_title AS meta_title, meta_descriptions AS meta_descriptions, attrs_boilerpipe_text AS attrs_boilerpipe_text, attrs_markdown AS attrs_markdown, attrs_readable_markdown AS attrs_readable_markdown, meta_canonical AS meta_canonical FROM crawler3.page_info_local FINAL PREWHERE (src_root_hash, src_unparsed) IN ((getAhrefsRootHashFromUnparsed(getAhrefsUnparsedNoserviceFromURL(\'https://pubs.usgs.gov/publication/70204463\')), getAhrefsUnparsedNoserviceFromURL(\'https://pubs.usgs.gov/publication/70204463\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/pubs.usgs.gov\/publication\/70204463","crawl_time":1775967119,"first_indexed_time":1696917047,"http_code":200,"src_unparsed":"gov,usgs!pubs,\/publication\/70204463 s443","src_root_hash":"17754418391278015812","history_drop_reason":null,"meta_title":"Bayesian statistics for beginners: A step-by-step approach","meta_descriptions":["Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data\/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference..."],"attrs_boilerpipe_text":"Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data\/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources.\nBayesian Statistics for Beginners\n is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.","attrs_markdown":"[Skip to main content](https:\/\/pubs.usgs.gov\/publication\/70204463#main-content)\n\n![U.S. flag](https:\/\/pubs.usgs.gov\/static\/img\/us_flag_small.be327dc2.png)\n\nAn official website of the United States government\n\nHere’s how you know\n\nHere’s how you know\n\n![Dot gov](https:\/\/pubs.usgs.gov\/static\/img\/icon-dot-gov.42b4ac46.svg)\n\n**Official websites use .gov**   \n A **.gov** website belongs to an official government organization in the United States.\n\n![Https](https:\/\/pubs.usgs.gov\/static\/img\/icon-https.73abd866.svg)\n\n**Secure .gov websites use HTTPS**   \n A **lock** ( A locked padlock ) or **https:\/\/** means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.\n\n[![USGS Home](https:\/\/pubs.usgs.gov\/static\/img\/USGS_logo.356d51b9.svg)](https:\/\/www.usgs.gov\/ \"Home\")\n\nMenu\n\n![close](https:\/\/pubs.usgs.gov\/static\/img\/close.fe3f13f6.svg)\n\n- [USGS Publications Warehouse](https:\/\/pubs.usgs.gov\/)\n- Explore\n  - [Explore recent publications by USGS authors](https:\/\/pubs.usgs.gov\/newpubs)\n  - [Browse all of Pubs Warehouse by publication type and year](https:\/\/pubs.usgs.gov\/browse\/)\n- Documentation\n  - [About](https:\/\/pubs.usgs.gov\/documentation\/about)\n  - [FAQs](https:\/\/pubs.usgs.gov\/documentation\/faq)\n  - [Web service documentation](https:\/\/pubs.usgs.gov\/documentation\/web_service_documentation)\n  - [Other resources](https:\/\/pubs.usgs.gov\/documentation\/other_resources)\n  - [Descriptions of US Geological Survey Report Series](https:\/\/pubs.usgs.gov\/documentation\/usgs_series)\n- [Contact](https:\/\/pubs.usgs.gov\/contact)\n- [Disclaimer](https:\/\/www.usgs.gov\/information-policies-and-instructions\/liability#future-ips)\n\n[![thumbnail](https:\/\/pubs.usgs.gov\/imgsizer\/_?f=PNG&u=https%3A%2F%2Fpubs.usgs.gov%2Fthumbnails%2Foutside_thumb.jpg&w=200&s=b'-UwlSoO6uTLlOIGHeaWA9bd7s68')](https:\/\/global.oup.com\/academic\/product\/bayesian-statistics-for-beginners-9780198841296?cc=us&lang=en& \"Go to Publisher Index Page for more information\")\n\n### Bayesian statistics for beginners: A step-by-step approach\nBy: Therese M. Donovan and Ruth M. Mickey\n\nMetrics\n\n[Web analytics dashboard](https:\/\/pubs.usgs.gov\/metrics\/publication\/70204463\/) [Metrics definitions](https:\/\/pubs.usgs.gov\/documentation\/faq#WhatMetricsAreAvailableForPublicationsInThePublicationsWarehouse)\n\n#### Links\n- More information:  [**Publisher Index Page**](https:\/\/global.oup.com\/academic\/product\/bayesian-statistics-for-beginners-9780198841296?cc=us&lang=en& \" Index Page\")\n- Download citation as: [RIS](https:\/\/pubs.usgs.gov\/publication\/70204463?mimetype=ris) \\| [Dublin Core](https:\/\/pubs.usgs.gov\/publication\/70204463?mimetype=dublincore)\n\n#### Abstract\nBayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data\/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources.  \n  \n*Bayesian Statistics for Beginners* is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.\n\n#### Suggested Citation\nDonovan, T.M., and Mickey, R.M., 2019, Bayesian statistics for beginners: A step-by-step approach, 432 p.\n\n|   |   |\n|---|---|\n| Publication type | Book |\n| Publication Subtype | Monograph |\n| Title | Bayesian statistics for beginners: A step-by-step approach |\n| ISBN | 9780198841296 |\n| Year Published | 2019 |\n| Language | English |\n| Publisher | Oxford University Press |\n| Contributing office(s) | Coop Res Unit Leetown |\n| Description | 432 p. |\n\n*\\*Disclaimer: English is the official language and authoritative version of all federal information.*\n\n[DOI Privacy Policy](https:\/\/www.doi.gov\/privacy) \\| [Legal](https:\/\/www.usgs.gov\/policies-and-notices) \\| [Accessibility](https:\/\/www.usgs.gov\/accessibility-and-us-geological-survey) \\| [Site Map](https:\/\/www.usgs.gov\/sitemap.html) \\| [Contact USGS](https:\/\/answers.usgs.gov\/)\n\n[U.S. Department of the Interior](https:\/\/www.doi.gov\/) \\| [DOI Inspector General](https:\/\/www.doioig.gov\/) \\| [White House](https:\/\/www.whitehouse.gov\/) \\| [E-gov](https:\/\/www.whitehouse.gov\/omb\/management\/egov\/) \\| [No Fear Act](https:\/\/www.doi.gov\/pmb\/eeo\/no-fear-act) \\| [FOIA](https:\/\/www.usgs.gov\/about\/organization\/science-support\/foia)","attrs_readable_markdown":"Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data\/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources.\n\n*Bayesian Statistics for Beginners* is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.","meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

Query:

Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

4 days ago

🤖

ROBOTS ALLOWED

Page Info Filters

Filter	Status	Condition	Details
HTTP status	PASS	`download_http_code = 200`	HTTP 200
Age cutoff	PASS	`download_stamp > now() - 6 MONTH`	0.1 months ago
History drop	PASS	`isNull(history_drop_reason)`	No drop reason
Spam/ban	PASS	`fh_dont_index != 1 AND ml_spam_score = 0`	ml_spam_score=0
Canonical	PASS	`meta_canonical IS NULL OR = '' OR = src_unparsed`	Not set

Page Details

Property	Value
URL	https://pubs.usgs.gov/publication/70204463
Last Crawled	2026-04-12 04:11:59 (4 days ago)
First Indexed	2023-10-10 05:50:47 (2 years ago)
HTTP Status Code	200
Meta Title	Bayesian statistics for beginners: A step-by-step approach
Meta Description	Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference...
Meta Canonical	null
Boilerpipe Text	Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.
Markdown	[Skip to main content](https://pubs.usgs.gov/publication/70204463#main-content) ![U.S. flag](https://pubs.usgs.gov/static/img/us_flag_small.be327dc2.png) An official website of the United States government Here’s how you know Here’s how you know ![Dot gov](https://pubs.usgs.gov/static/img/icon-dot-gov.42b4ac46.svg) Official websites use .gov A .gov website belongs to an official government organization in the United States. ![Https](https://pubs.usgs.gov/static/img/icon-https.73abd866.svg) Secure .gov websites use HTTPS A lock ( A locked padlock ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites. [![USGS Home](https://pubs.usgs.gov/static/img/USGS_logo.356d51b9.svg)](https://www.usgs.gov/ "Home") Menu ![close](https://pubs.usgs.gov/static/img/close.fe3f13f6.svg) - [USGS Publications Warehouse](https://pubs.usgs.gov/) - Explore - [Explore recent publications by USGS authors](https://pubs.usgs.gov/newpubs) - [Browse all of Pubs Warehouse by publication type and year](https://pubs.usgs.gov/browse/) - Documentation - [About](https://pubs.usgs.gov/documentation/about) - [FAQs](https://pubs.usgs.gov/documentation/faq) - [Web service documentation](https://pubs.usgs.gov/documentation/web_service_documentation) - [Other resources](https://pubs.usgs.gov/documentation/other_resources) - [Descriptions of US Geological Survey Report Series](https://pubs.usgs.gov/documentation/usgs_series) - [Contact](https://pubs.usgs.gov/contact) - [Disclaimer](https://www.usgs.gov/information-policies-and-instructions/liability#future-ips) [![thumbnail](https://pubs.usgs.gov/imgsizer/_?f=PNG&u=https%3A%2F%2Fpubs.usgs.gov%2Fthumbnails%2Foutside_thumb.jpg&w=200&s=b'-UwlSoO6uTLlOIGHeaWA9bd7s68')](https://global.oup.com/academic/product/bayesian-statistics-for-beginners-9780198841296?cc=us&lang=en& "Go to Publisher Index Page for more information") ### Bayesian statistics for beginners: A step-by-step approach By: Therese M. Donovan and Ruth M. Mickey Metrics [Web analytics dashboard](https://pubs.usgs.gov/metrics/publication/70204463/) [Metrics definitions](https://pubs.usgs.gov/documentation/faq#WhatMetricsAreAvailableForPublicationsInThePublicationsWarehouse) #### Links - More information: [Publisher Index Page](https://global.oup.com/academic/product/bayesian-statistics-for-beginners-9780198841296?cc=us&lang=en& " Index Page") - Download citation as: [RIS](https://pubs.usgs.gov/publication/70204463?mimetype=ris) \\| [Dublin Core](https://pubs.usgs.gov/publication/70204463?mimetype=dublincore) #### Abstract Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields. #### Suggested Citation Donovan, T.M., and Mickey, R.M., 2019, Bayesian statistics for beginners: A step-by-step approach, 432 p. \| \| \| \|---\|---\| \| Publication type \| Book \| \| Publication Subtype \| Monograph \| \| Title \| Bayesian statistics for beginners: A step-by-step approach \| \| ISBN \| 9780198841296 \| \| Year Published \| 2019 \| \| Language \| English \| \| Publisher \| Oxford University Press \| \| Contributing office(s) \| Coop Res Unit Leetown \| \| Description \| 432 p. \| \Disclaimer: English is the official language and authoritative version of all federal information.* [DOI Privacy Policy](https://www.doi.gov/privacy) \\| [Legal](https://www.usgs.gov/policies-and-notices) \\| [Accessibility](https://www.usgs.gov/accessibility-and-us-geological-survey) \\| [Site Map](https://www.usgs.gov/sitemap.html) \\| [Contact USGS](https://answers.usgs.gov/) [U.S. Department of the Interior](https://www.doi.gov/) \\| [DOI Inspector General](https://www.doioig.gov/) \\| [White House](https://www.whitehouse.gov/) \\| [E-gov](https://www.whitehouse.gov/omb/management/egov/) \\| [No Fear Act](https://www.doi.gov/pmb/eeo/no-fear-act) \\| [FOIA](https://www.usgs.gov/about/organization/science-support/foia)
Readable Markdown	Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.
Shard	12 (laksa)
Root Hash	17754418391278015812
Unparsed URL	gov,usgs!pubs,/publication/70204463 s443