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Quirk T.J. Cummings S. Excel 2013 for Health Services Management Statistics: A Guide to Solving Practical Problems

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Quirk T.J. Cummings S. Excel 2013 for Health Services Management Statistics: A Guide to Solving Practical Problems
Springer, 2016. — 265 p. — (Excel for Statistics). — ISBN: 9783319289847, 9783319289854.
This book shows how Microsoft Excel is able to teach health services management statistics effectively. Similar to the previously published Excel 2010 for Health Services Management Statistics, it is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical health services management problems. If understanding statistics isn’t your strongest suit, you are not especially mathematically-inclined, or if you are wary of computers, this is the right book for you.
Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in health services management courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2010 for Health Services Management Statistics: A Guide to Solving Practical Problems capitalizes on these improvements by teaching students and managers how to apply Excel to statistical techniques necessary in their courses and work.
Each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand health services management problems. Practice problems are provided at the end of each chapter with their solutions in an Appendix. Separately, there is a full Practice Test (with answers in an Appendix) that allows readers to test what they have learned.
Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
Random Number Generator
Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
One-Group t-Test for the Mean
Two-Group t-Test of the Difference of the Means for Independent Groups
Correlation and Simple Linear Regression
Multiple Correlation and Multiple Regression
One-Way Analysis of Variance (ANOVA)
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