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PHYSICS 366: Statistical Methods in Astrophysics

Course notes and resources for Stanford University graduate lecture course PHYSICS 366.

Course Description

This course is intended to provide an introduction to modern statistical methodology, and its applications to problems in astrophysics and cosmology, and is aimed at graduate students intending to do research in this area. We strongly encourage most first and second year students working in KIPAC to take the course. Our goal is to provide a background that will be directly relevant to the kind of problems that typical KIPAC students will encounter in their research.

Course Objectives

Our goal is that students taking this course will:

  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.

Information

For anyone

For Stanford students

Content

The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.

Contact

All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.

About

Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods

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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
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, 'i');
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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
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Readme
GPL-2.0 license
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
Resources
Readme
GPL-2.0 license
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
Resources
Readme
GPL-2.0 license
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, 'i');
if (__m === '*' || __re.test(location.href)) {
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
Resources
Readme
GPL-2.0 license
Activity
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2 watching
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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");
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
Resources
Readme
GPL-2.0 license
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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PHYSICS 366: Statistical Methods in Astrophysics
Course notes and resources for Stanford University graduate lecture course PHYSICS 366.
Course Description
This course is intended to provide an introduction to modern
statistical methodology, and its applications to problems in
astrophysics and cosmology, and is aimed at graduate students
intending to do research in this area. We
strongly encourage most first and second year students working in
KIPAC to take the course. Our goal is to provide a background that
will be directly relevant to the kind of problems that typical KIPAC
students will encounter in their research.
Course Objectives
Our goal is that students taking this course will:
  • develop familiarity in working with various types of astronomical data.
  • understand the role of modeling in data analysis.
  • develop facility with various types of inference from data.
  • be able to critically evaluate and apply commonly used statistical methodologies.
  • be able to apply advanced statistical reasoning to problems they are likely to encounter in their research.
Information
For anyone
For Stanford students
Content
The course content can be browsed on GitHub, or you can clone the repository and run the notebooks locally. The easiest way to navigate the materials is through the links in the Schedule document.
Contact
All materials Copyright 2015, 2017, 2019 Adam Mantz and Phil Marshall, and distributed for copying and extension under the GPLv2 License, unless otherwise noted. If you have any feedback for us, please write us an issue. If you would like to help us improve this course, please do fork this repo and submit a pull request.
About
Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
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Readme
GPL-2.0 license
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