Foundations of Agnostic Statistics
$38.99 USD
- Authors:
- Peter M. Aronow, Yale University, Connecticut
- Benjamin T. Miller, Yale University, Connecticut
- Date Published: February 2019
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
- format: Adobe eBook Reader
- isbn: 9781316836309
Find out more about Cambridge eBooks
$
38.99 USD
Adobe eBook Reader
Other available formats:
Paperback, Hardback
Looking for an inspection copy?
This title is not currently available on inspection
-
Reflecting a sea change in how empirical research has been conducted over the past three decades, Foundations of Agnostic Statistics presents an innovative treatment of modern statistical theory for the social and health sciences. This book develops the fundamentals of what the authors call agnostic statistics, which considers what can be learned about the world without assuming that there exists a simple generative model that can be known to be true. Aronow and Miller provide the foundations for statistical inference for researchers unwilling to make assumptions beyond what they or their audience would find credible. Building from first principles, the book covers topics including estimation theory, regression, maximum likelihood, missing data, and causal inference. Using these principles, readers will be able to formally articulate their targets of inquiry, distinguish substantive assumptions from statistical assumptions, and ultimately engage in cutting-edge quantitative empirical research that contributes to human knowledge.
Read more- Provides a rigorous and targeted mathematical introduction to the statistics underlying modern statistical methodology in the social and health sciences
- Prepares readers to go on to advanced study in statistical methodology, including in causal inference, nonparametric statistics, and econometrics
- Develops the fundamentals of 'agnostic statistics' - an approach that asks what can be learned about the world under minimal assumptions
Customer reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity
×Product details
- Date Published: February 2019
- format: Adobe eBook Reader
- isbn: 9781316836309
- contains: 35 b/w illus.
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Introduction
Part I. Probability:
1. Probability theory
2. Summarizing distributions
Part II. Statistics:
3. Learning from random samples
4. Regression
5. Parametric models
Part III. Identification:
6. Missing data
7. Causal inference.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email [email protected]
Register Sign in» Proceed
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.
Continue ×Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.
×