Statistical Analysis: Microsoft Excel 2013

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

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 Analysis Of Variance: Further Issues
Chapter 12 Experimental Design And Anova
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