**Use Excel 2013’s statistical tools
to transform your data into knowledge**

Conrad Carlberg shows how to
use Excel 2013 to perform core statistical tasks every business
professional, student, and researcher should master. Using
real-world examples, Carlberg helps you choose the right technique
for each problem and get the most out of Excel’s statistical
features, including recently introduced consistency functions.
Along the way, he clarifies confusing statistical terminology and
helps you avoid common mistakes.

You’ll learn how to use correlation and regression, analyze
variance and covariance, and test statistical hypotheses using the
normal, binomial, t, and F distributions. To help you make accurate
inferences based on samples from a population, this edition adds
two more chapters on inferential statistics, covering crucial
topics ranging from experimental design to the statistical power of
F tests.

Becoming an expert with Excel statistics has never been easier! You’ll find crystal-clear instructions, insider insights, and complete step-by-step projects—all complemented by extensive web-based resources.

Master Excel’s most useful descriptive and inferential statistical tools

Tell the truth with statistics—and recognize when others don’t

Accurately summarize sets of values

Infer a population’s characteristics from a sample’s frequency distribution

Explore correlation and regression to learn how variables move in tandem

Use Excel consistency functions such as STDEV.S() and STDEV.P()

Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in

Use ANOVA to test differences between more than two means

Explore statistical power by manipulating mean differences, standard errors, directionality, and alpha

Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2013 shortcuts

- About This eBook
- Title Page
- Copyright Page
- Contents at a Glance
- Table of Contents
- About the Author
- Dedication
- Acknowledgments
- We Want to Hear from You!
- Reader Services
- Introduction
- 1. About Variables and Values
- 2. How Values Cluster Together
- 3. Variability: How Values Disperse
- 4. How Variables Move Jointly: Correlation
- 5. How Variables Classify Jointly: Contingency Tables
- 6. Telling the Truth with Statistics
- 7. Using Excel with the Normal Distribution
- 8. Testing Differences Between Means: The Basics
- 9. Testing Differences Between Means: Further Issues
- 10. Testing Differences Between Means: The Analysis of Variance
- 11. Analysis of Variance: Further Issues
- 12. Experimental Design and ANOVA
- 13. Statistical Power
- 14. Multiple Regression Analysis and Effect Coding: The Basics
- 15. Multiple Regression Analysis and Effect Coding: Further Issues
- 16. Analysis of Covariance: The Basics
- 17. Analysis of Covariance: Further Issues
- Index