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Probability

The repo is still under development. Scheduled completion is 01-31-20

About this repo

This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.

Intended use

Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:

  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables

Data access

Access to data is provided through the Jupyter notebook templates.

Contributing

Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:

  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch

If your analysis makes sense and provides an innovative or original view of the subject we will request the following:

  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information

tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.

What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.

The hammerdirt infrastructure:

These are the main components of the hammerdirt! infrastructure:

  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:

About hammerdirt!

Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.

Joining hammerdirt!

  1. see hammerdirt.ch in the docs tab "members"

About

Analysis of beach litter survey results using different probability methods

www.plagespropres.ch/

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
Resources
Readme
Activity
Stars
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0 watching
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0 forks
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
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0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
Resources
Readme
Activity
Stars
0 stars
Watchers
0 watching
Forks
0 forks
Report repository
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Packages
Contributors
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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Probability
The repo is still under development. Scheduled completion is 01-31-20
About this repo
This repo is part of the 2020-2021 beach litter surveillance project and part of the hammerdirt! infrastructure. Access is public.
Intended use
Applying different probability distributions and methods to survey data. Completed analysis projects are displayed on the hammerdirt! app and the appropriate client app. Analysis is focussed on the probability distribtuion of objects found at the regional level:
  1. Indentifying appropriate distributions for data
  2. Defining the PDF for each regional level and all data
  3. Defining the PDF for key objects at regional levels
  4. Using the probability distributions to explore/explain observed values
  5. Understanding the relationship of independent variables and their effect on the PDF
  6. Identifying relevant independent variables
Data access
Access to data is provided through the Jupyter notebook templates.
Contributing
Follow these steps if you would like to submit a completed analysis or visualisation and have it included in a publication or on a client app:
  1. Clone the repo
  2. Start a branch titled <yourname_probability>
  3. In the notebook make sure to change the "save_prefix" value
  4. Complete your analysis
  5. On your local generate .html output of the notebook
  6. Send the .html doc to roger@hammerdirt.ch
If your analysis makes sense and provides an innovative or original view of the subject we will request the following:
  1. A summary of your analysis
  2. References/bibliography
  3. Full contact information
tips: Stay on topic. Follow the template model. There are/will be a couple examples to follow in the repo. If you follow that and your analysis makes sense it will be easy for us to generate the document for the application.
What happens next?: Your analysis will be visible by others interested in the topic, if our clients choose your analysis then it will be included in any publications and you will be credited in the publication.
The hammerdirt infrastructure:
These are the main components of the hammerdirt! infrastructure:
  1. Data storage and distribution through the API:
  1. Data entry and management:
  1. Data visualisation, communication:
  1. Version control and collaboration:
About hammerdirt!
Hammerdirt! is a non-profit organisation based in Switzerland and dedicated to the collection, analysis and distribution of environmental data.
Joining hammerdirt!
  1. see hammerdirt.ch in the docs tab "members"
About
Analysis of beach litter survey results using different probability methods
www.plagespropres.ch/
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