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PHYS366: Special Topics in Astrophysics: Statistical Methods

Course notes and resources for Stanford University graduate lecture course PHYS366.

Course Description

The course is intended to provide an introduction to modern statistical methodology and its applications to problems in astrophysics and cosmology. The course is aimed at graduate students intending to do research in astrophysics and cosmology, and 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.

Preliminaries

Lessons

  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations

You can help write a glossary of terms used in the lectures here.

Contact

  • Phil Marshall
  • Risa Wechsler

All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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

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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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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GPL-2.0 license
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PHYS366: Special Topics in Astrophysics: Statistical Methods
Course notes and resources for Stanford University graduate lecture course PHYS366.
Course Description
The course is intended to provide an introduction to modern
statistical methodology and its applications to problems in
astrophysics and cosmology. The course is aimed at graduate students
intending to do research in astrophysics and cosmology, and 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.
Preliminaries
Lessons
  • Exploring Data
  • Understanding from Data
  • Inference in Practice: PDF Characterization
  • Inference in Practice: Sampling Techniques
  • Inference in Practice: Coping with Complications
  • Inference in Practice: Evaluating Models
  • Applications in Astroparticle Physics
  • Applications in Cosmology
  • Machine Learning
  • Project Presenations
You can help write a glossary of terms used in the lectures here.
Contact
  • Phil Marshall
  • Risa Wechsler
All materials Copyright 2015 Phil Marshall, Adam Mantz, Elisabeth Krause, and Risa Wechsler, and distributed for copying and extension under the GPLv2 License. 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.
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Course notes and resources for Stanford University gradutate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods 
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