MARC details
| 000 -LEADER |
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| fixed length control field |
02724nam a22002177a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20230104124649.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230104b ||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780367624279 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
300.15195 |
| Item number |
GAR |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Garson, G. David |
| 245 ## - TITLE STATEMENT |
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| Title |
Data analytics for the social sciences: |
| Remainder of title |
applications in R |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc. |
Routledge |
| Place of publication, distribution, etc. |
New York |
| Date of publication, distribution, etc. |
2022 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xviii, 686 p. |
| 365 ## - TRADE PRICE |
|---|
| Price type code |
GBP |
| Price amount |
74.99 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Table of Contents<br/>1. Using and Abusing Data Analytics in Social Science 2. Statistical Analytics with R, Part 1 3. Statistical Analytics with R, Part 2 4. Classification and Regression Trees in R 5. Random Forests 6. Modeling and Machine Learning 7. Neural Network Models and Deep Learning 8. Network Analysis 9. Text Analytics; Appendix 1. Introduction to R and R Studio Appendix 2. Data Used in this Book |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Data Analytics for the Social Sciences is an introductory, graduate-level treatment of data analytics for social science. It features applications in the R language, arguably the fastest growing and leading statistical tool for researchers.<br/><br/>The book starts with an ethics chapter on the uses and potential abuses of data analytics. Chapters 2 and 3 show how to implement a broad range of statistical procedures in R. Chapters 4 and 5 deal with regression and classification trees and with random forests. Chapter 6 deals with machine learning models and the "caret" package, which makes available to the researcher hundreds of models. Chapter 7 deals with neural network analysis, and Chapter 8 deals with network analysis and visualization of network data. A final chapter treats text analysis, including web scraping, comparative word frequency tables, word clouds, word maps, sentiment analysis, topic analysis, and more. All empirical chapters have two "Quick Start" exercises designed to allow quick immersion in chapter topics, followed by "In Depth" coverage. Data are available for all examples and runnable R code is provided in a "Command Summary". An appendix provides an extended tutorial on R and RStudio. Almost 30 online supplements provide information for the complete book, "books within the book" on a variety of topics, such as agent-based modeling.<br/><br/>Rather than focusing on equations, derivations, and proofs, this book emphasizes hands-on obtaining of output for various social science models and how to interpret the output. It is suitable for all advanced level undergraduate and graduate students learning statistical data analysis. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
R (Computer program language) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Social sciences--Statistical methods |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Social sciences--Statistical methods--Data processing |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |