Excel 2019 for Physical Sciences Statistics, 2nd Edition Front Cover

Excel 2019 for Physical Sciences Statistics, 2nd Edition

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  • Length: 264 pages
  • Edition: 2
  • Publisher:
  • Publication Date: 2021-03-09
  • ISBN-10: 3030632377
  • ISBN-13: 9783030632373

Book Description

This book shows the capabilities of Microsoft Excel in teaching physical science statistics effectively. Similar to the previously published Excel 2016 for Physical Sciences Statistics, this book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical physical science problems. If understanding statistics isn’t the reader’s strongest suit, the reader is not mathematically inclined, or if the reader is new to computers or to Excel, this is the book to start off with.

Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in physical science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past. Excel 2019 for Physical Sciences 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.

In this new edition, each chapter explains statistical formulas and directs the reader to use Excel commands to solve specific, easy-to-understand physical science 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.

Table of contents

1. Sample Size, Mean, Standard Deviation, and Standard Error of the Mean
2. Random Number Generator
3. Confidence Interval About the Mean Using the TINV Function and Hypothesis Testing
4. One-Group t-Test for the Mean
5. Two-Group t-Test of the Difference of the Means for Independent Groups
6. Correlation and Simple Linear Regression
7. Multiple Correlation and Multiple Regression
8. One-Way Analysis of Variance (ANOVA)

About The Author

Howard F. Horton

Meghan H. Quirk

Thomas J. Quirk

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