The art of statistics : how to learn from data / David Spiegelhalter.
Material type:
TextNew York : Basic Books, 2021Edition: First US Trade Paperback editionDescription: xvi, 426 pages : illustrations ; 21 cmContent type: - text
- unmediated
- volume
- 9781541675704
- 23 519.5
- QA276.12 .S654 2021
| Cover image | Item type | Current library | Home library | Collection | Shelving location | Call number | Materials specified | Vol info | URL | Copy number | Status | Notes | Date due | Barcode | Item holds | Item hold queue priority | Course reserves | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Books
|
High School Learning Resource Center General Circulation | Non-fiction | QA 276.12 .S654 2021 (Browse shelf(Opens below)) | 1 | Available | HS14799 |
Browsing High School Learning Resource Center shelves,Shelving location: General Circulation,Collection: Non-fiction Close shelf browser (Hides shelf browser)
|
|
|
|
|
No cover image available |
|
||
| QA 157 .S74a 2022 c.2 Algebra II: all-in-one for dummies/ | QA 157 .W556 2022 Algebra I : review and workbook / | QA 276 .R85 2023 Statistics all-in-one for Dummies / | QA 276.12 .S654 2021 The art of statistics : how to learn from data / | QA 303.2 .G638 2012 c.2 The cartoon guide to calculus | QA 445 .G67 2024 The cartoon guide to geometry / | QA 445 .R53 2018 Schaum's outlines. Geometry : includes plane, analytic, and transformational geometries / |
Includes bibliographical references (pages 407-418) and index.
Introduction -- Getting things done in proportion : categorical data and percentages --
Summarizing and communicating numbers, lots of numbers --
Why are we looking at data anyway? : populations and measurement --
What causes what? --
Modelling relationships using regression --
Algorithms, analytics and prediction --
How sure can we be about what is going on? : estimates and intervals --
Probability : the language of uncertainty and variability --
Putting probability and statistics together --
Answering questions and claiming discoveries --
Learning from experience the Bayesian way --
How things go wrong --
How we can do statistics better --
In conclusion.
Shows how to apply statistical reasoning to real-world problems. This isn't simply memorizing formulas or using the tools in a spreadsheet: he emphasizes the importance of clarifying questions, assumptions, and expectations, and--more importantly--knowing how to responsibly interpret the results the software generates.-- Source other than the Library of Congress.
There are no comments on this title.