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Key features:
Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R
Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R
Provides a step-by-step guide that you can replicate using your own data
Includes exercises in every chapter for course use or self-study
Focuses on practical-based approaches to statistical inference rather than mathematical formulae
Supplemented by an R package, including all data
As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.
Key features:
Each chapter has the most up-to-date and simple option available for each task, assuming minimal prerequisites and no previous experience in R
Makes extensive use of the Tidyverse, the group of packages that has revolutionized the use of R
Provides a step-by-step guide that you can replicate using your own data
Includes exercises in every chapter for course use or self-study
Focuses on practical-based approaches to statistical inference rather than mathematical formulae
Supplemented by an R package, including all data
As the title suggests, this book is highly applied in nature, and is designed as a toolbox for the reader. It can be used in methods and data science courses, at both the undergraduate and graduate levels. It will be equally useful for a university student pursuing a PhD, political consultants, or a public official, all of whom need to transform their datasets into substantive and easily interpretable conclusions.
I Introduction to R
1. Basic R
2. Data Management
3. Data Visualization
4. Data Loading
II Models
5. Linear Models
6. Case Selection Based on Regressions
7. Panel Data
8. Logistic Models
9. Survival Models
10. Causal Inference
III Applications
11. Advanced Political Data Management
12. Web Mining
13. Quantitative Analysis of Political Texts
14. Networks
15. Principal Component Analysis
16. Maps and Spatial Data
Erscheinungsjahr: | 2022 |
---|---|
Genre: | Politikwissenschaften |
Rubrik: | Wissenschaften |
Medium: | Taschenbuch |
Inhalt: | Einband - flex.(Paperback) |
ISBN-13: | 9780367818838 |
ISBN-10: | 0367818833 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Urdinez, Francisco
Cruz, Andres |
Hersteller: | Chapman and Hall/CRC |
Maße: | 254 x 178 x 25 mm |
Von/Mit: | Francisco Urdinez (u. a.) |
Erscheinungsdatum: | 30.05.2022 |
Gewicht: | 0,858 kg |
I Introduction to R
1. Basic R
2. Data Management
3. Data Visualization
4. Data Loading
II Models
5. Linear Models
6. Case Selection Based on Regressions
7. Panel Data
8. Logistic Models
9. Survival Models
10. Causal Inference
III Applications
11. Advanced Political Data Management
12. Web Mining
13. Quantitative Analysis of Political Texts
14. Networks
15. Principal Component Analysis
16. Maps and Spatial Data
Erscheinungsjahr: | 2022 |
---|---|
Genre: | Politikwissenschaften |
Rubrik: | Wissenschaften |
Medium: | Taschenbuch |
Inhalt: | Einband - flex.(Paperback) |
ISBN-13: | 9780367818838 |
ISBN-10: | 0367818833 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Urdinez, Francisco
Cruz, Andres |
Hersteller: | Chapman and Hall/CRC |
Maße: | 254 x 178 x 25 mm |
Von/Mit: | Francisco Urdinez (u. a.) |
Erscheinungsdatum: | 30.05.2022 |
Gewicht: | 0,858 kg |