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Beschreibung
This open access book prepares current and aspiring analytics professionals to effectively address this need by curating key concepts spanning the entire analytics lifecycle, along with step-by-step instructions for their applications to real-world problems, using ubiquitous and freely available open-source software. This book does not assume prior knowledge of statistics, how to query databases, or how to write performant code; early chapters include an introduction to R and SQL as well as an overview of statistical foundations.
Human capital is an organization¿s most important asset. Without the knowledge and skills of people, an organization can accomplish nothing. The acquisition, development, and retention of critical talent has become increasingly more complex and challenging, and organizations are making significant investments to gain a deeper, data-informed understanding of organizational phenomena impacting the bottom line.
By the end of this book, readers will be able to:
¿ Design and conduct empirical research
¿ Query and wrangle data using SQL
¿ Profile, clean, and analyze data using R
¿ Apply appropriate statistical and ML models to a range of people analytics use cases
¿ Package and present analyses to communicate impactful insights to stakeholders
¿ Design and conduct empirical research
¿ Query and wrangle data using SQL
¿ Profile, clean, and analyze data using R
¿ Apply appropriate statistical and ML models to a range of people analytics use cases
¿ Package and present analyses to communicate impactful insights to stakeholders
This open access book prepares current and aspiring analytics professionals to effectively address this need by curating key concepts spanning the entire analytics lifecycle, along with step-by-step instructions for their applications to real-world problems, using ubiquitous and freely available open-source software. This book does not assume prior knowledge of statistics, how to query databases, or how to write performant code; early chapters include an introduction to R and SQL as well as an overview of statistical foundations.
Human capital is an organization¿s most important asset. Without the knowledge and skills of people, an organization can accomplish nothing. The acquisition, development, and retention of critical talent has become increasingly more complex and challenging, and organizations are making significant investments to gain a deeper, data-informed understanding of organizational phenomena impacting the bottom line.
By the end of this book, readers will be able to:
¿ Design and conduct empirical research
¿ Query and wrangle data using SQL
¿ Profile, clean, and analyze data using R
¿ Apply appropriate statistical and ML models to a range of people analytics use cases
¿ Package and present analyses to communicate impactful insights to stakeholders
¿ Design and conduct empirical research
¿ Query and wrangle data using SQL
¿ Profile, clean, and analyze data using R
¿ Apply appropriate statistical and ML models to a range of people analytics use cases
¿ Package and present analyses to communicate impactful insights to stakeholders
Über den Autor
Craig Starbuck is a leading expert in people analytics, who has built and led successful people analytics teams at Roku, Robinhood, Mastercard, Equifax, and TD Ameritrade, after spending a decade in various data engineering and analytics positions in the banking and health care industries. He is the Co-Founder and Chief Data Scientist at OrgAcuity, a tech company with a mission to democratize access to people analytics, and a Member of the Society for Industrial and Organizational Psychology (SIOP).
Zusammenfassung
Provides a curated and organized compendium of theory, practical applications
Includes data sets, code, and functions in R, for immediate use
Instructs end-to-end analytics lifecycle, step by step
This book is open access, which means that you have free and unlimited access
Inhaltsverzeichnis
1. Getting Started.- 2. Introduction to R.- 3. Introduction to SQL.- 4. Research Design.- 5. Measurement & Sampling.- 6. Data Preparation.- 7. Descriptive Statistics.- 8. Statistical Inference.- 9. Analysis of Differences.- 10. Linear Regression.- 11. Linear Model Extensions.- 12. Logistic Regression.- 13. Predictive Modeling.- 14. Unsupervised Learning.- 15. Data Visualization.- 16. Data Storytelling.
Details
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xvi
380 S. 5 s/w Illustr. 250 farbige Illustr. 380 p. 255 illus. 250 illus. in color. |
| ISBN-13: | 9783031286766 |
| ISBN-10: | 3031286766 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: | Starbuck, Craig |
| Auflage: | 1st ed. 2023 |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing Springer International Publishing AG |
| Maße: | 235 x 155 x 22 mm |
| Von/Mit: | Craig Starbuck |
| Erscheinungsdatum: | 09.07.2023 |
| Gewicht: | 0,598 kg |
Über den Autor
Craig Starbuck is a leading expert in people analytics, who has built and led successful people analytics teams at Roku, Robinhood, Mastercard, Equifax, and TD Ameritrade, after spending a decade in various data engineering and analytics positions in the banking and health care industries. He is the Co-Founder and Chief Data Scientist at OrgAcuity, a tech company with a mission to democratize access to people analytics, and a Member of the Society for Industrial and Organizational Psychology (SIOP).
Zusammenfassung
Provides a curated and organized compendium of theory, practical applications
Includes data sets, code, and functions in R, for immediate use
Instructs end-to-end analytics lifecycle, step by step
This book is open access, which means that you have free and unlimited access
Inhaltsverzeichnis
1. Getting Started.- 2. Introduction to R.- 3. Introduction to SQL.- 4. Research Design.- 5. Measurement & Sampling.- 6. Data Preparation.- 7. Descriptive Statistics.- 8. Statistical Inference.- 9. Analysis of Differences.- 10. Linear Regression.- 11. Linear Model Extensions.- 12. Logistic Regression.- 13. Predictive Modeling.- 14. Unsupervised Learning.- 15. Data Visualization.- 16. Data Storytelling.
Details
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xvi
380 S. 5 s/w Illustr. 250 farbige Illustr. 380 p. 255 illus. 250 illus. in color. |
| ISBN-13: | 9783031286766 |
| ISBN-10: | 3031286766 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | Paperback |
| Einband: | Kartoniert / Broschiert |
| Autor: | Starbuck, Craig |
| Auflage: | 1st ed. 2023 |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing Springer International Publishing AG |
| Maße: | 235 x 155 x 22 mm |
| Von/Mit: | Craig Starbuck |
| Erscheinungsdatum: | 09.07.2023 |
| Gewicht: | 0,598 kg |
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