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Statistical Analysis with Excel For Dummies, 4th Edition

Book Description

Learn all of Excel's statistical tools

Test your hypotheses and draw conclusions

Use Excel to give meaning to your data

Use Excel to interpret stats

Statistical analysis with Excel is incredibly useful—and this book shows you that it can be easy, too! You'll discover how to use Excel's perfectly designed tools to analyze and understand data, predict trends, make decisions, and more. Tackle the technical aspects of Excel and start using them to interpret your data!


  • Covers Excel 2016 for Windows® & Mac® users
  • Check out new Excel stuff
  • Make sense of worksheets
  • Create shortcuts
  • Tool around with analysis
  • Use Quick Statistics
  • Graph your data
  • Work with probability
  • Handle random variables

Table of Contents

    1. Cover
    2. Introduction
      1. About This Book
      2. What You Can Safely Skip
      3. Foolish Assumptions
      4. How This Book Is Organized
      5. Icons Used in This Book
      6. Where to Go from Here
    3. Part 1: Getting Started with Statistical Analysis with Excel: A Marriage Made in Heaven
      1. Chapter 1: Evaluating Data in the Real World
        1. The Statistical (and Related) Notions You Just Have to Know
        2. Inferential Statistics: Testing Hypotheses
        3. What’s New in Excel 2016?
        4. What’s Old in Excel 2016?
        5. Knowing the Fundamentals
        6. What’s New in This Edition?
      2. Chapter 2: Understanding Excel’s Statistical Capabilities
        1. Getting Started
        2. Setting Up for Statistics
        3. Accessing Commonly Used Functions
    4. Part 2: Describing Data
      1. Chapter 3: Show and Tell: Graphing Data
        1. Why Use Graphs?
        2. Some Fundamentals
        3. Excel’s Graphics (Chartics?) Capabilities
        4. Becoming a Columnist
        5. Slicing the Pie
        6. Drawing the Line
        7. Adding a Spark
        8. Passing the Bar
        9. The Plot Thickens
        10. Finding Another Use for the Scatter Chart
        11. Tasting the Bubbly
        12. Taking Stock
        13. Scratching the Surface
        14. On the Radar
        15. Growing a Treemap and Bursting Some Sun
        16. Building a Histogram
        17. Ordering Columns: Pareto
        18. Of Boxes and Whiskers
        19. 3D Maps
      2. Chapter 4: Finding Your Center
        1. Means: The Lore of Averages
        2. Medians: Caught in the Middle
        3. Statistics à la Mode
      3. Chapter 5: Deviating from the Average
        1. Measuring Variation
        2. Back to the Roots: Standard Deviation
        3. Related Functions
      4. Chapter 6: Meeting Standards and Standings
        1. Catching Some Zs
        2. Where Do You Stand?
      5. Chapter 7: Summarizing It All
        1. Counting Out
        2. The Long and Short of It
        3. Getting Esoteric
        4. Tuning In the Frequency
        5. Can You Give Me a Description?
        6. Be Quick About It!
        7. Instant Statistics
      6. Chapter 8: What’s Normal?
        1. Hitting the Curve
        2. A Distinguished Member of the Family
        3. Graphing a Standard Normal Distribution
    5. Part 3: Drawing Conclusions from Data
      1. Chapter 9: The Confidence Game: Estimation
        1. Understanding Sampling Distributions
        2. An EXTREMELY Important Idea: The Central Limit Theorem
        3. The Limits of Confidence
        4. Fit to a t
      2. Chapter 10: One-Sample Hypothesis Testing
        1. Hypotheses, Tests, and Errors
        2. Hypothesis Tests and Sampling Distributions
        3. Catching Some Z’s Again
        4. t for One
        5. Visualizing a t-Distribution
        6. Testing a Variance
        7. Visualizing a Chi-Square Distribution
      3. Chapter 11: Two-Sample Hypothesis Testing
        1. Hypotheses Built for Two
        2. Revisited
        3. t for Two
        4. A Matched Set: Hypothesis Testing for Paired Samples
        5. Testing Two Variances
        6. Visualizing the F-Distribution
      4. Chapter 12: Testing More Than Two Samples
        1. Testing More Than Two
        2. Another Kind of Hypothesis, Another Kind of Test
      5. Chapter 13: Slightly More Complicated Testing
        1. Cracking the Combinations
        2. Cracking the Combinations Again
        3. Two Kinds of Variables … at Once
        4. Using Excel with a Mixed Design
        5. Graphing the Results
        6. After the ANOVA
      6. Chapter 14: Regression: Linear and Multiple
        1. The Plot of Scatter
        2. Graphing Lines
        3. Regression: What a Line!
        4. Worksheet Functions for Regression
        5. Data Analysis Tool: Regression
        6. Juggling Many Relationships at Once: Multiple Regression
        7. Excel Tools for Multiple Regression
      7. Chapter 15: Correlation: The Rise and Fall of Relationships
        1. Scatterplots Again
        2. Understanding Correlation
        3. Correlation and Regression
        4. Testing Hypotheses About Correlation
        5. Worksheet Functions for Correlation
        6. Data Analysis Tool: Correlation
        7. Data Analysis Tool: Covariance
        8. Testing Hypotheses About Correlation
      8. Chapter 16: It’s About Time
        1. A Series and Its Components
        2. A Moving Experience
        3. How To Be a Smoothie, Exponentially
        4. One-Click Forecasting!
      9. Chapter 17: Non-Parametric Statistics
        1. Independent Samples
        2. Matched Samples
        3. Correlation: Spearman’s rS
        4. A Heads-Up
    6. Part 4: Probability
      1. Chapter 18: Introducing Probability
        1. What Is Probability?
        2. Compound Events
        3. Conditional Probability
        4. Large Sample Spaces
        5. Worksheet Functions
        6. Random Variables: Discrete and Continuous
        7. Probability Distributions and Density Functions
        8. The Binomial Distribution
        9. Worksheet Functions
        10. Hypothesis Testing with the Binomial Distribution
        11. The Hypergeometric Distribution
      2. Chapter 19: More on Probability
        1. Discovering Beta
        2. Poisson
        3. Working with Gamma
        4. Exponential
      3. Chapter 20: A Career in Modeling
        1. Modeling a Distribution
        2. A Simulating Discussion
    7. Part 5: The Part of Tens
      1. Chapter 21: Ten Statistical and Graphical Tips and Traps
        1. Significant Doesn’t Always Mean Important
        2. Trying to Not Reject a Null Hypothesis Has a Number of Implications
        3. Regression Isn’t Always Linear
        4. Extrapolating Beyond a Sample Scatterplot Is a Bad Idea
        5. Examine the Variability Around a Regression Line
        6. A Sample Can Be Too Large
        7. Consumers: Know Your Axes
        8. Graphing a Categorical Variable as Though It’s a Quantitative Variable Is Just Wrong
        9. Whenever Appropriate, Include Variability in Your Graph
        10. Be Careful When Relating Statistics Textbook Concepts to Excel
      2. Chapter 22: Ten Things (Twelve, Actually) That Just Didn’t Fit in Any Other Chapter
        1. Graphing the Standard Error of the Mean
        2. Probabilities and Distributions
        3. Drawing Samples
        4. Testing Independence: The True Use of CHISQ.TEST
        5. Logarithmica Esoterica
        6. Sorting Data
      3. Appendix A: When Your Worksheet Is a Database
        1. Introducing Excel Databases
        2. Counting and Retrieving
        3. Arithmetic
        4. Statistics
        5. Pivot Tables
      4. Appendix B: The Analysis of Covariance
        1. Covariance: A Closer Look
        2. Why You Analyze Covariance
        3. How You Analyze Covariance
        4. ANCOVA in Excel
        5. And One More Thing
    8. About the Author
    9. Advertisement Page
    10. Connect with Dummies
    11. End User License Agreement