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1. Shard Calculation

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Calculated Shard: 56 (from laksa178)

2. Crawled Status Check

Query:

curl -X POST \
  'http://laksa056.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://ben-lambert.com/a-students-guide-to-bayesian-statistics/\')), getAhrefsUnparsedNoserviceFromURL(\'https://ben-lambert.com/a-students-guide-to-bayesian-statistics/\'))) FORMAT JSONEachRow'

Response:

{"found_url":"https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/","crawl_time":1776123636,"first_indexed_time":1554029943,"http_code":200,"src_unparsed":"com,ben-lambert!\/a-students-guide-to-bayesian-statistics\/ s443","src_root_hash":"10121848307901357456","history_drop_reason":null,"meta_title":"A Student’s Guide to Bayesian Statistics –","meta_descriptions":["The book is now published and available from Amazon. The problem set questions and answers for the book are available here. The data for the problem questions is available here. There are a few things I wish I did better in the first edition, and have made note of these as they come to mind or…"],"attrs_boilerpipe_text":"The book is now published and available from\nAmazon\n. The problem set questions and answers for the book are available\nhere\n. The data for the problem questions is available\nhere\n.\nThere are a few things I wish I did better in the first edition, and have made\nnote\n of these as they come to mind or when people get in touch to inform me of errata.\nThe distribution zoo\nI created a shiny app called ‘\nThe distribution zoo\n‘ that allows a user to investigate distributions. This app allows a user to:\nDynamically change the parameters of 24 distributions, ranging from fairly simple cases (for example, normal or Poisson), up to more complex cases such as the LKJ correlation distribution, and investigate how these parameters affect the resultant distributional properties, including plots of the probability density function or probability mass function, histograms of the sampling distribution for some cases where the PDFs are hard to visualise, and cumulative distribution functions where appropriate.\nContains \ndynamic\ncode snippets in R, Python, Matlab, Mathematica and Stan, which reflect changes in the parameter values. Importantly, for each distribution and parameter set, these functions should give equivalent results across all five languages. For me, this is really useful, since different languages have different parameterisations and some (Python!) have really non-standard parameterisations, which can make translating code from one language to another tricky.\nContains detailed and vetted formulae for each distribution giving useful properties. These formulae are also available in LaTeX form to make using them in articles, reports and so on simpler.\nBecause it’s been deployed to the web, you can use this app anywhere. Look at the zoo of distributions on your laptop, tablet or smartphone!\nThis code is fresh and so, whilst it has been tested extensively, errors may occur. If you find any, please create an issue on the Github repo\nhere\n.","attrs_markdown":"Menu\n\n#\n\n[Skip to content](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/#content)\n\n- [About](https:\/\/ben-lambert.com\/about\/)\n- [Bayesian statistics](https:\/\/ben-lambert.com\/bayesian\/)\n  - [Imperial Bayesian lectures](https:\/\/ben-lambert.com\/imperial-bayesian-lectures\/)\n  - [Bayesian short course](https:\/\/ben-lambert.com\/bayesian-short-course\/)\n  - [Bayesian lectures syllabus](https:\/\/ben-lambert.com\/bayesian-lectures\/)\n  - [Bayesian lecture slides](https:\/\/ben-lambert.com\/bayesian-lecture-slides\/)\n  - [A Student’s Guide to Bayesian Statistics](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n  - [How I make stats videos?](https:\/\/ben-lambert.com\/how-i-make-stats-videos\/)\n- [Epidemiology](https:\/\/ben-lambert.com\/epidemiology\/)\n- [Biology](https:\/\/ben-lambert.com\/biology\/)\n- [Inference in evolution](https:\/\/ben-lambert.com\/evolution\/)\n- [HIV evolution](https:\/\/ben-lambert.com\/evolutionary-epidemiology\/)\n- [Econometrics](https:\/\/ben-lambert.com\/econometrics\/)\n  - [Econometrics course problem sets and data](https:\/\/ben-lambert.com\/econometrics-course-problem-sets-and-data\/)\n  - [Econometrics and statistics books](https:\/\/ben-lambert.com\/econometrics-and-statistics-books\/)\n  - [How I make stats videos?](https:\/\/ben-lambert.com\/how-i-make-stats-videos\/)\n#\n[Skip to content](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/#content)\n\n- [About](https:\/\/ben-lambert.com\/about\/)\n- [Bayesian statistics](https:\/\/ben-lambert.com\/bayesian\/)\n  - [Imperial Bayesian lectures](https:\/\/ben-lambert.com\/imperial-bayesian-lectures\/)\n  - [Bayesian short course](https:\/\/ben-lambert.com\/bayesian-short-course\/)\n  - [Bayesian lectures syllabus](https:\/\/ben-lambert.com\/bayesian-lectures\/)\n  - [Bayesian lecture slides](https:\/\/ben-lambert.com\/bayesian-lecture-slides\/)\n  - [A Student’s Guide to Bayesian Statistics](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n  - [How I make stats videos?](https:\/\/ben-lambert.com\/how-i-make-stats-videos\/)\n- [Epidemiology](https:\/\/ben-lambert.com\/epidemiology\/)\n- [Biology](https:\/\/ben-lambert.com\/biology\/)\n- [Inference in evolution](https:\/\/ben-lambert.com\/evolution\/)\n- [HIV evolution](https:\/\/ben-lambert.com\/evolutionary-epidemiology\/)\n- [Econometrics](https:\/\/ben-lambert.com\/econometrics\/)\n  - [Econometrics course problem sets and data](https:\/\/ben-lambert.com\/econometrics-course-problem-sets-and-data\/)\n  - [Econometrics and statistics books](https:\/\/ben-lambert.com\/econometrics-and-statistics-books\/)\n  - [How I make stats videos?](https:\/\/ben-lambert.com\/how-i-make-stats-videos\/)\n\n# A Student’s Guide to Bayesian Statistics\nThe book is now published and available from [Amazon](https:\/\/www.amazon.co.uk\/Students-Guide-Bayesian-Statistics\/dp\/1473916364\/). The problem set questions and answers for the book are available [here](https:\/\/ben-lambert.com\/wp-content\/uploads\/2019\/03\/bayesianbook_problemsanswers_including_errata.pdf). The data for the problem questions is available [here](https:\/\/ben-lambert.com\/wp-content\/uploads\/2018\/08\/all_data.zip).\n\nThere are a few things I wish I did better in the first edition, and have made [note](https:\/\/ben-lambert.com\/wp-content\/uploads\/2019\/03\/errata.pdf) of these as they come to mind or when people get in touch to inform me of errata.\n\n###### The distribution zoo\nI created a shiny app called ‘[The distribution zoo](https:\/\/ben18785.shinyapps.io\/distribution-zoo\/)‘ that allows a user to investigate distributions. This app allows a user to:\n\n- Dynamically change the parameters of 24 distributions, ranging from fairly simple cases (for example, normal or Poisson), up to more complex cases such as the LKJ correlation distribution, and investigate how these parameters affect the resultant distributional properties, including plots of the probability density function or probability mass function, histograms of the sampling distribution for some cases where the PDFs are hard to visualise, and cumulative distribution functions where appropriate.\n- Contains *dynamic* code snippets in R, Python, Matlab, Mathematica and Stan, which reflect changes in the parameter values. Importantly, for each distribution and parameter set, these functions should give equivalent results across all five languages. For me, this is really useful, since different languages have different parameterisations and some (Python!) have really non-standard parameterisations, which can make translating code from one language to another tricky.\n- Contains detailed and vetted formulae for each distribution giving useful properties. These formulae are also available in LaTeX form to make using them in articles, reports and so on simpler.\n\nBecause it’s been deployed to the web, you can use this app anywhere. Look at the zoo of distributions on your laptop, tablet or smartphone\\!\n\nThis code is fresh and so, whilst it has been tested extensively, errors may occur. If you find any, please create an issue on the Github repo [here](https:\/\/github.com\/ben18785\/distribution-viewer\/issues).\n\n### Share this:\n- [Share on X (Opens in new window) X](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/?share=twitter&nb=1)\n- [Share on Facebook (Opens in new window) Facebook](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/?share=facebook&nb=1)\n\nLike Loading...\n\n[Blog at WordPress.com.](https:\/\/wordpress.com\/?ref=footer_blog)\n\n- [Subscribe](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n  [Subscribed](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n  - [![](https:\/\/s0.wp.com\/i\/logo\/wpcom-gray-white.png?m=1479929237i)](https:\/\/ben-lambert.com\/)\n  - Already have a WordPress.com account? [Log in now.](https:\/\/wordpress.com\/log-in?redirect_to=https%3A%2F%2Fr-login.wordpress.com%2Fremote-login.php%3Faction%3Dlink%26back%3Dhttps%253A%252F%252Fben-lambert.com%252Fa-students-guide-to-bayesian-statistics%252F)\n- - [![](https:\/\/s0.wp.com\/i\/logo\/wpcom-gray-white.png?m=1479929237i)](https:\/\/ben-lambert.com\/)\n  - [Subscribe](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n    [Subscribed](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n  - [Sign up](https:\/\/wordpress.com\/start\/)\n  - [Log in](https:\/\/wordpress.com\/log-in?redirect_to=https%3A%2F%2Fr-login.wordpress.com%2Fremote-login.php%3Faction%3Dlink%26back%3Dhttps%253A%252F%252Fben-lambert.com%252Fa-students-guide-to-bayesian-statistics%252F)\n  - [Copy shortlink](https:\/\/wp.me\/P7f47C-9Y)\n  - [Report this content](https:\/\/wordpress.com\/abuse\/?report_url=https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n  - [View post in Reader](https:\/\/wordpress.com\/reader\/blogs\/107025120\/posts\/618)\n  - [Manage subscriptions](https:\/\/subscribe.wordpress.com\/)\n  - [Collapse this bar](https:\/\/ben-lambert.com\/a-students-guide-to-bayesian-statistics\/)\n\n%d\n\n![](https:\/\/pixel.wp.com\/b.gif?v=noscript)","attrs_readable_markdown":"The book is now published and available from [Amazon](https:\/\/www.amazon.co.uk\/Students-Guide-Bayesian-Statistics\/dp\/1473916364\/). The problem set questions and answers for the book are available [here](https:\/\/ben-lambert.com\/wp-content\/uploads\/2019\/03\/bayesianbook_problemsanswers_including_errata.pdf). The data for the problem questions is available [here](https:\/\/ben-lambert.com\/wp-content\/uploads\/2018\/08\/all_data.zip).\n\nThere are a few things I wish I did better in the first edition, and have made [note](https:\/\/ben-lambert.com\/wp-content\/uploads\/2019\/03\/errata.pdf) of these as they come to mind or when people get in touch to inform me of errata.\n\n###### The distribution zoo\nI created a shiny app called ‘[The distribution zoo](https:\/\/ben18785.shinyapps.io\/distribution-zoo\/)‘ that allows a user to investigate distributions. This app allows a user to:\n\n- Dynamically change the parameters of 24 distributions, ranging from fairly simple cases (for example, normal or Poisson), up to more complex cases such as the LKJ correlation distribution, and investigate how these parameters affect the resultant distributional properties, including plots of the probability density function or probability mass function, histograms of the sampling distribution for some cases where the PDFs are hard to visualise, and cumulative distribution functions where appropriate.\n- Contains *dynamic* code snippets in R, Python, Matlab, Mathematica and Stan, which reflect changes in the parameter values. Importantly, for each distribution and parameter set, these functions should give equivalent results across all five languages. For me, this is really useful, since different languages have different parameterisations and some (Python!) have really non-standard parameterisations, which can make translating code from one language to another tricky.\n- Contains detailed and vetted formulae for each distribution giving useful properties. These formulae are also available in LaTeX form to make using them in articles, reports and so on simpler.\n\nBecause it’s been deployed to the web, you can use this app anywhere. Look at the zoo of distributions on your laptop, tablet or smartphone\\!\n\nThis code is fresh and so, whilst it has been tested extensively, errors may occur. If you find any, please create an issue on the Github repo [here](https:\/\/github.com\/ben18785\/distribution-viewer\/issues).","meta_canonical":null}

3. Robots.txt Check

Query:

Response:

4. Spam/Ban Check

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Response:

5. Seen Status Check

ℹ️ Skipped - page is already crawled

📄

INDEXABLE

✅

CRAWLED

7 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`	0.3 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://ben-lambert.com/a-students-guide-to-bayesian-statistics/
Last Crawled	2026-04-13 23:40:36 (7 days ago)
First Indexed	2019-03-31 10:59:03 (7 years ago)
HTTP Status Code	200
Meta Title	A Student’s Guide to Bayesian Statistics –
Meta Description	The book is now published and available from Amazon. The problem set questions and answers for the book are available here. The data for the problem questions is available here. There are a few things I wish I did better in the first edition, and have made note of these as they come to mind or…
Meta Canonical	null
Boilerpipe Text	The book is now published and available from Amazon . The problem set questions and answers for the book are available here . The data for the problem questions is available here . There are a few things I wish I did better in the first edition, and have made note of these as they come to mind or when people get in touch to inform me of errata. The distribution zoo I created a shiny app called ‘ The distribution zoo ‘ that allows a user to investigate distributions. This app allows a user to: Dynamically change the parameters of 24 distributions, ranging from fairly simple cases (for example, normal or Poisson), up to more complex cases such as the LKJ correlation distribution, and investigate how these parameters affect the resultant distributional properties, including plots of the probability density function or probability mass function, histograms of the sampling distribution for some cases where the PDFs are hard to visualise, and cumulative distribution functions where appropriate. Contains dynamic code snippets in R, Python, Matlab, Mathematica and Stan, which reflect changes in the parameter values. Importantly, for each distribution and parameter set, these functions should give equivalent results across all five languages. For me, this is really useful, since different languages have different parameterisations and some (Python!) have really non-standard parameterisations, which can make translating code from one language to another tricky. Contains detailed and vetted formulae for each distribution giving useful properties. These formulae are also available in LaTeX form to make using them in articles, reports and so on simpler. Because it’s been deployed to the web, you can use this app anywhere. Look at the zoo of distributions on your laptop, tablet or smartphone! This code is fresh and so, whilst it has been tested extensively, errors may occur. If you find any, please create an issue on the Github repo here .
Markdown	Menu # [Skip to content](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/#content) - [About](https://ben-lambert.com/about/) - [Bayesian statistics](https://ben-lambert.com/bayesian/) - [Imperial Bayesian lectures](https://ben-lambert.com/imperial-bayesian-lectures/) - [Bayesian short course](https://ben-lambert.com/bayesian-short-course/) - [Bayesian lectures syllabus](https://ben-lambert.com/bayesian-lectures/) - [Bayesian lecture slides](https://ben-lambert.com/bayesian-lecture-slides/) - [A Student’s Guide to Bayesian Statistics](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/) - [How I make stats videos?](https://ben-lambert.com/how-i-make-stats-videos/) - [Epidemiology](https://ben-lambert.com/epidemiology/) - [Biology](https://ben-lambert.com/biology/) - [Inference in evolution](https://ben-lambert.com/evolution/) - [HIV evolution](https://ben-lambert.com/evolutionary-epidemiology/) - [Econometrics](https://ben-lambert.com/econometrics/) - [Econometrics course problem sets and data](https://ben-lambert.com/econometrics-course-problem-sets-and-data/) - [Econometrics and statistics books](https://ben-lambert.com/econometrics-and-statistics-books/) - [How I make stats videos?](https://ben-lambert.com/how-i-make-stats-videos/) # [Skip to content](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/#content) - [About](https://ben-lambert.com/about/) - [Bayesian statistics](https://ben-lambert.com/bayesian/) - [Imperial Bayesian lectures](https://ben-lambert.com/imperial-bayesian-lectures/) - [Bayesian short course](https://ben-lambert.com/bayesian-short-course/) - [Bayesian lectures syllabus](https://ben-lambert.com/bayesian-lectures/) - [Bayesian lecture slides](https://ben-lambert.com/bayesian-lecture-slides/) - [A Student’s Guide to Bayesian Statistics](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/) - [How I make stats videos?](https://ben-lambert.com/how-i-make-stats-videos/) - [Epidemiology](https://ben-lambert.com/epidemiology/) - [Biology](https://ben-lambert.com/biology/) - [Inference in evolution](https://ben-lambert.com/evolution/) - [HIV evolution](https://ben-lambert.com/evolutionary-epidemiology/) - [Econometrics](https://ben-lambert.com/econometrics/) - [Econometrics course problem sets and data](https://ben-lambert.com/econometrics-course-problem-sets-and-data/) - [Econometrics and statistics books](https://ben-lambert.com/econometrics-and-statistics-books/) - [How I make stats videos?](https://ben-lambert.com/how-i-make-stats-videos/) # A Student’s Guide to Bayesian Statistics The book is now published and available from [Amazon](https://www.amazon.co.uk/Students-Guide-Bayesian-Statistics/dp/1473916364/). The problem set questions and answers for the book are available [here](https://ben-lambert.com/wp-content/uploads/2019/03/bayesianbook_problemsanswers_including_errata.pdf). The data for the problem questions is available [here](https://ben-lambert.com/wp-content/uploads/2018/08/all_data.zip). There are a few things I wish I did better in the first edition, and have made [note](https://ben-lambert.com/wp-content/uploads/2019/03/errata.pdf) of these as they come to mind or when people get in touch to inform me of errata. ###### The distribution zoo I created a shiny app called ‘[The distribution zoo](https://ben18785.shinyapps.io/distribution-zoo/)‘ that allows a user to investigate distributions. This app allows a user to: - Dynamically change the parameters of 24 distributions, ranging from fairly simple cases (for example, normal or Poisson), up to more complex cases such as the LKJ correlation distribution, and investigate how these parameters affect the resultant distributional properties, including plots of the probability density function or probability mass function, histograms of the sampling distribution for some cases where the PDFs are hard to visualise, and cumulative distribution functions where appropriate. - Contains dynamic code snippets in R, Python, Matlab, Mathematica and Stan, which reflect changes in the parameter values. Importantly, for each distribution and parameter set, these functions should give equivalent results across all five languages. For me, this is really useful, since different languages have different parameterisations and some (Python!) have really non-standard parameterisations, which can make translating code from one language to another tricky. - Contains detailed and vetted formulae for each distribution giving useful properties. These formulae are also available in LaTeX form to make using them in articles, reports and so on simpler. Because it’s been deployed to the web, you can use this app anywhere. Look at the zoo of distributions on your laptop, tablet or smartphone\! This code is fresh and so, whilst it has been tested extensively, errors may occur. If you find any, please create an issue on the Github repo [here](https://github.com/ben18785/distribution-viewer/issues). ### Share this: - [Share on X (Opens in new window) X](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/?share=twitter&nb=1) - [Share on Facebook (Opens in new window) Facebook](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/?share=facebook&nb=1) Like Loading... [Blog at WordPress.com.](https://wordpress.com/?ref=footer_blog) - [Subscribe](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/) [Subscribed](https://ben-lambert.com/a-students-guide-to-bayesian-statistics/) - [![](https://s0.wp.com/i/logo/wpcom-gray-white.png?m=1479929237i)](https://ben-lambert.com/) - Already have a WordPress.com account? 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Readable Markdown	The book is now published and available from [Amazon](https://www.amazon.co.uk/Students-Guide-Bayesian-Statistics/dp/1473916364/). The problem set questions and answers for the book are available [here](https://ben-lambert.com/wp-content/uploads/2019/03/bayesianbook_problemsanswers_including_errata.pdf). The data for the problem questions is available [here](https://ben-lambert.com/wp-content/uploads/2018/08/all_data.zip). There are a few things I wish I did better in the first edition, and have made [note](https://ben-lambert.com/wp-content/uploads/2019/03/errata.pdf) of these as they come to mind or when people get in touch to inform me of errata. ###### The distribution zoo I created a shiny app called ‘[The distribution zoo](https://ben18785.shinyapps.io/distribution-zoo/)‘ that allows a user to investigate distributions. This app allows a user to: - Dynamically change the parameters of 24 distributions, ranging from fairly simple cases (for example, normal or Poisson), up to more complex cases such as the LKJ correlation distribution, and investigate how these parameters affect the resultant distributional properties, including plots of the probability density function or probability mass function, histograms of the sampling distribution for some cases where the PDFs are hard to visualise, and cumulative distribution functions where appropriate. - Contains dynamic code snippets in R, Python, Matlab, Mathematica and Stan, which reflect changes in the parameter values. Importantly, for each distribution and parameter set, these functions should give equivalent results across all five languages. For me, this is really useful, since different languages have different parameterisations and some (Python!) have really non-standard parameterisations, which can make translating code from one language to another tricky. - Contains detailed and vetted formulae for each distribution giving useful properties. These formulae are also available in LaTeX form to make using them in articles, reports and so on simpler. Because it’s been deployed to the web, you can use this app anywhere. Look at the zoo of distributions on your laptop, tablet or smartphone\! This code is fresh and so, whilst it has been tested extensively, errors may occur. If you find any, please create an issue on the Github repo [here](https://github.com/ben18785/distribution-viewer/issues).
Shard	56 (laksa)
Root Hash	10121848307901357456
Unparsed URL	com,ben-lambert!/a-students-guide-to-bayesian-statistics/ s443