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Statistical Analysis: Microsoft Excel 2013by Conrad Carlberg
Synopses & Reviews
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.
Statistical Analysis: Microsoft Excel 2013 is a hands-on tutorial of elementary to intermediate statistics. With a downloadable workbook for each chapter of the book, you will learn statistics by doing — and avoid the torture that so many students and professionals face when learning statistics. By using Excel, a familiar and comfortable interface, you will be able to play with data and immediately see your results.
Author Conrad Carlberg has a doctorate in statistics, has taught the subject at the college level, and has written about aspects of it in other books on Excel. In this book, he thoroughly teaches statistics in a practical manner. He also discusses how to recognize statistics that are grounded in a sound experimental design.
About the Author
Conrad Carlberg started writing about Excel, and its use in quantitative analysis, before workbooks had worksheets. As a graduate student, he had the great good fortune to learn something about statistics from the wonderfully gifted Gene Glass. He remembers much of that and has learned more since. This is a book he has wanted to write for years, and he is grateful for the opportunity.
Table of Contents
Chapter 1: About Variables and Values
Chapter 2: How Values Cluster Together
Chapter 3: Variability: How Values Disperse
Chapter 4: How Variables Move Jointly: Correlation
Chapter 5: How Variables Classify Jointly: Contingency Tables
Chapter 6: Telling the Truth with Statistics
Chapter 7: Using Excel with the Normal Distribution
Chapter 8: Testing Differences between Means: The Basics
Chapter 9: Testing Differences between Means: Further Issues
Chapter 10: Testing Differences between Means: The Analysis of Variance
Chapter 11: Experimental Design and ANOVA
Chapter 12: Analysis of Variance: Further Issues
Chapter 13: Statistical Power
Chapter 14: Multiple Regression Analysis and Effect Coding: The Basics
Chapter 15: Multiple Regression Analysis: Further Issues
Chapter 16: Analysis of Covariance: The Basics
Chapter 17: Analysis of Covariance: Further Issues
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