## Book Description

You too can understand the statistics of life, even if you're math-challenged!

What do you need to calculate? Manufacturing output? A curve for test scores? Sports stats? You and Excel can do it, and this non-intimidating guide shows you how. It demystifies the different types of statistics, how Excel functions and formulas work, the meaning of means and medians, how to interpret your figures, and more — in plain English.

• Getting there — learn how variables, samples, and probability are used to get the information you want

• Excel tricks — find out what's built into the program to help you work with Excel formulas

• Playing with worksheets — get acquainted with the worksheet functions for each step

• Graphic displays — present your data as pie graphs, bar graphs, line graphs, or scatter plots

• What's normal? — understand normal distribution and probability

• Hyping hypotheses — learn to use hypothesis testing with means and variables

• When regression is progress — discover when and how to use regression for forecasting

• What are the odds — work with probability, random variables, and binomial distribution

Open the book and find:

• Ten statistical and graphical tips and traps

• The difference between descriptive and inferential statistics

• Why graphs are good

• How to measure variations

• What standard scores are and why they're used

• When to use two-sample hypothesis testing

• How to use correlations

• Different ways of working with probability

3. Author's Acknowledgments
4. Publisher's Acknowledgments
5. Introduction
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
6. I. Statistics and Excel: A Marriage Made in Heaven
1. 1. Evaluating Data in the Real World
1. 1.1. The Statistical (And Related) Notions You Just Have to Know
2. 1.2. Inferential Statistics: Testing Hypotheses
3. 1.3. What's New in Excel?
4. 1.4. Some Things about Excel You Absolutely Have to Know
5. 1.5. What's New in This Edition?
2. 2. Understanding Excel's Statistical Capabilities
1. 2.1. Getting Started
2. 2.2. Setting Up for Statistics
3. 2.3. Accessing Commonly Used Functions
7. II. Describing Data
1. 3. Show and Tell: Graphing Data
1. 3.1. Why Use Graphs?
2. 3.2. Some Fundamentals
3. 3.3. Excel's Graphics Capabilities
4. 3.4. Becoming a Columnist
5. 3.5. Slicing the Pie
6. 3.6. Drawing the Line
7. 3.7. Passing the Bar
8. 3.8. The Plot Thickens
1. 4.1. Means: The Lore of Averages
1. 4.1.1. Calculating the mean
2. 4.1.2. AVERAGE and AVERAGEA
3. 4.1.3. AVERAGEIF and AVERAGEIFS
4. 4.1.4. TRIMMEAN
5. 4.1.5. Other means to an end
2. 4.2. Medians: Caught in the Middle
3. 4.3. Statistics À La Mode
3. 5. Deviating from the Average
1. 5.1. Measuring Variation
2. 5.2. Back to the Roots: Standard Deviation
1. 5.2.1. Population standard deviation
2. 5.2.2. STDEVP and STDEVPA
3. 5.2.3. Sample standard deviation
4. 5.2.4. STDEV and STDEVA
5. 5.2.5. The missing functions: STDEVIF and STDEVIFS
3. 5.3. Related Functions
4. 6. Meeting Standards and Standings
1. 6.1. Catching Some Zs
2. 6.2. Where Do You Stand?
5. 7. Summarizing It All
1. 7.1. Counting Out
2. 7.2. The Long and Short of It
3. 7.3. Getting Esoteric
4. 7.4. Tuning In the Frequency
5. 7.5. Can You Give Me a Description?
6. 7.6. Instant Statistics
6. 8. What's Normal?
1. 8.1. Hitting the Curve
2. 8.2. A Distinguished Member of the Family
8. III. Drawing Conclusions from Data
1. 9. The Confidence Game: Estimation
1. 9.1. What is a Sampling Distribution?
2. 9.2. An EXTREMELY Important Idea: The Central Limit Theorem
3. 9.3. The Limits of Confidence
4. 9.4. Fit to a t
2. 10. One-Sample Hypothesis Testing
1. 10.1. Hypotheses, Tests, and Errors
2. 10.2. Catching Some Zs Again
3. 10.3. t for One
4. 10.4. Testing a Variance
3. 11. Two-Sample Hypothesis Testing
1. 11.1. Hypotheses Built for Two
2. 11.2. Sampling Distributions Revisited
3. 11.3. t for Two
4. 11.4. A Matched Set: Hypothesis Testing for Paired Samples
5. 11.5. Testing Two Variances
4. 12. Testing More Than Two Samples
1. 12.1. Testing More Than Two
1. 12.1.1. A thorny problem
2. 12.1.2. A solution
3. 12.1.3. Meaningful relationships
4. 12.1.4. After the F-test
5. 12.1.5. Data analysis tool: Anova: Single Factor
6. 12.1.6. Comparing the means
2. 12.2. Another Kind of Hypothesis, Another Kind of Test
5. 13. Slightly More Complicated Testing
1. 13.1. Cracking the Combinations
2. 13.2. Cracking the Combinations Again
6. 14. Regression: Linear and Multiple
1. 14.1. The Plot of Scatter
2. 14.2. Graphing Lines
3. 14.3. Regression: What a Line!
1. 14.3.1. Using regression for forecasting
2. 14.3.2. Variation around the regression line
3. 14.3.3. Testing hypotheses about regression
4. 14.4. Worksheet Functions for Regression
1. 14.4.1. SLOPE, INTERCEPT, STEYX
2. 14.4.2. FORECAST
3. 14.4.3. Array function: TREND
4. 14.4.4. Array function: LINEST
5. 14.5. Data Analysis Tool: Regression
6. 14.6. Juggling Many Relationships at Once: Multiple Regression
7. 14.7. Excel Tools for Multiple Regression
7. 15. Correlation: The Rise and Fall of Relationships
1. 15.1. Scatterplots Again
2. 15.2. Understanding Correlation
3. 15.3. Correlation and Regression
4. 15.4. Testing Hypotheses About Correlation
5. 15.5. Worksheet Functions for Correlation
6. 15.6. Data Analysis Tool: Correlation
1. 15.6.1. Tabled output
7. 15.7. Data Analysis Tool: Covariance
8. 15.8. Testing Hypotheses About Correlation
9. IV. Working with Probability
1. 16. Introducing Probability
1. 16.1. What is Probability?
2. 16.2. Compound Events
3. 16.3. Conditional Probability
4. 16.4. Large Sample Spaces
5. 16.5. Worksheet Functions
6. 16.6. Random Variables: Discrete and Continuous
7. 16.7. Probability Distributions and Density Functions
8. 16.8. The Binomial Distribution
9. 16.9. Worksheet Functions
10. 16.10. Hypothesis Testing with the Binomial Distribution
11. 16.11. The Hypergeometric Distribution
2. 17. More on Probability
1. 17.1. Beta
2. 17.2. Poisson
3. 17.3. Gamma
4. 17.4. Exponential
3. 18. A Career in Modeling
1. 18.1. Modeling a Distribution
2. 18.2. A Simulating Discussion
1. 18.2.1. Taking a chance: The Monte Carlo method
3. 18.2.3. Simulating the Central Limit Theorem
10. V. The Part of Tens
1. 19. Ten Statistical and Graphical Tips and Traps
2. 20. Ten Things (Twelve, Actually) That Didn't Fit in Any Other Chapter
1. 20.1. Some Forecasting
2. 20.2. Graphing the Standard Error of the Mean
3. 20.3. Probabilities and Distributions
4. 20.4. Drawing Samples
5. 20.5. Testing Independence: The True Use of CHITEST
6. 20.6. Logarithmica Esoterica
1. 20.6.1. What is a logarithm?
2. 20.6.2. What is e?
3. 20.6.3. LOGNORMDIST
5. 20.6.5. Array Function: LOGEST
6. 20.6.6. Array Function: GROWTH
7. 20.7. When Your Data Live Elsewhere
11. A. When Your Worksheet Is a Database
1. A.1. Introducing Excel Databases
2. A.2. Counting and Retrieving
1. A.2.1. DCOUNT and DCOUNTA
2. A.2.2. DGET
3. A.3. Arithmetic
4. A.4. Statistics
5. A.5. Pivot Tables
12. B. The Analysis of Covariance
1. B.1. Covariance: A Closer Look
2. B.2. Why You Analyze Covariance
3. B.3. How You Analyze Covariance
4. B.4. ANCOVA in Excel
5. B.5. And One More Thing
13. C. Of Stems, Leaves, Boxes, Whiskers, and Smoothies

## Product Information

• Title: Statistical Analysis with Excel® For Dummies®, 2nd Edition
• Author(s): Joseph Schmuller
• Release date: June 2009
• Publisher(s): For Dummies
• ISBN: 9780470454060