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The fundamentals of people analytics...

Starbuck, Craig.

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The fundamentals of people analytics = with applications in R /

Record Type:	Electronic resources : Monograph/item
Title/Author:	The fundamentals of people analytics/ by Craig Starbuck.
Reminder of title:	with applications in R /
Author:	Starbuck, Craig.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	xvi, 380 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Human capital - Statistical methods. -
Online resource:	https://doi.org/10.1007/978-3-031-28674-2
ISBN:	9783031286742

The fundamentals of people analytics = with applications in R /
Starbuck, Craig.

The fundamentals of people analyticswith applications in R /[electronic resource] :by Craig Starbuck. - Cham :Springer International Publishing :2023. - xvi, 380 p. :ill., digital ;24 cm.

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.

Open access.

ISBN: 9783031286742

Standard No.: 10.1007/978-3-031-28674-2doiSubjects--Topical Terms:

3663781
Human capital
--Statistical methods.

LC Class. No.: HD4904.7

Dewey Class. No.: 658.30727

The fundamentals of people analytics = with applications in R /
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505 0 $a 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.
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