Visualizing Health Care Statistics: A Data-Mining Approach is an engaging, introduction to health care statistics that demonstrates how to visualize health care statistics by using Microsoft Excel and R-Project (open source statistical software) along with hands-on examples using real-world data. In each chapter, readers are encouraged to apply statistical knowledge to real-world health care situations. Through this approach, the reader develops data gathering and analysis skills, while learning how to report and present the data in an impactful way.
Key Features:
* A breadth of real-world, current health data, including global examples to put health care into a worldwide context.
* An introduction to the modern computer software that readers will use in their careers to apply statistics, including Excel and open-source R-Project.
* A data-mining approach helps readers understand how big data can be used systematically to increase health care quality and safety while cutting costs.
* Data visualization in each chapter to highlight the importance of reporting data to end-users in a meaningful way.
* Alignment with new CAHIIM standards, and notes those standards throughout the text.
* An ideal resource for preparing for the Registered Health Information Technician (RHIT) exam.
* Helpful appendices including common abbreviations used in statistics, formulas for health care statistics, resources for further information, CAHIIM competency exercises, and more.
Product details
- Hardback | 450 pages
- 213.36 x 271.78 x 17.78mm | 680.39g
- 09 Oct 2020
- Jones and Bartlett Publishers, Inc
- Sudbury, United States
- English
- Revised
- 2nd Revised edition
- 1284197522
- 9781284197525
- 3,210,485
Download Visualizing Health Care Statistics: A Data-Mining Approach (9781284197525).pdf, available at ebookdownloadfree.co for free.
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