图书简介
Based on Neil J. Salkind?s bestselling text, Statistics for People Who (Think They) Hate Statistics, this adapted Excel 2016 version presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Researchers and students uncomfortable with the analysis portion of their work will appreciate the book?s unhurried pace and thorough, friendly presentation. Opening with an introduction to Excel 2016, including functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques and then walks them through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. New to the Fourth Edition: A new chapter 20 dealing with large data sets using Excel functions and pivot tables, and illustrating how certain databases and other categories of functions and formulas can help make the data in big data sets easier to work with and the results more understandable. New chapter-ending exercises are included and contain a variety of levels of application. Additional TechTalks have been added to help students master Excel 2016. A new, chapter-ending Real World Stats feature shows readers how statistics is applied in the everyday world. Basic maths instruction and practice exercises for those who need to brush up on their math skills are included in the appendix.
Part I: Yippee! I?m in Statistics \\ Chapter 1: Statistics or Sadistics? It?s Up to You \\ Why Statistics? \\ A Five-Minute History of Statistics \\ Statistics: What It Is (and Isn?t) \\ Tooling Around With the Analysis ToolPak \\ What Am I Doing in a Statistics Class? \\ Ten Ways to Use This Book (and Learn Statistics at the Same Time!) \\ About Those Icons \\ Key to Difficulty Icons \\ Key to ?How Much Excel? Icons \\ Little Chapter 1a. All You Need to Know About Formulas and Functions \\ What?s a Formula? \\ What?s a Function? \\ Little Chapter 1b. All You Need to Know About Using the Amazing Analysis ToolPak \\ A Look at the Analysis ToolPak \\ Don?t Have It? \\ Little Chapter 1c. Mac Lovers Rejoice! StatPlus: The Mac Alternative to the Analysis ToolPak \\ Little Chapter 1c. For Mac Lovers Who are Still using Version 2011: Rejoice!! And, for Mac Lovers Who are new to Version 2016, Rejoice More!!! \\ Part II: Sigma Freud and Descriptive Statistics \\ Chapter 2: Computing and Understanding Averages: Means to an End \\ Computing the Mean \\ Computing a Weighted Mean \\ Computing the Median \\ Computing the Mode \\ Using the Amazing Analysis ToolPak to Compute Descriptive Statistics \\ When to Use What \\ Chapter 3: Vive la Différence: Understanding Variability \\ Why Understanding Variability Is Important \\ Computing the Range \\ Computing the Standard Deviation \\ Computing the Variance \\ And Now... Using Excel?s VAR.S Function \\ The Standard Deviation Versus the Variance \\ Using the Amazing Analysis ToolPak (Again!) \\ Chapter 4: A Picture Really Is Worth a Thousand Words \\ Why Illustrate Data? \\ Ten Ways to a Great Figure (Eat Less and Exercise More?) \\ First Things First: Creating a Frequency Distribution \\ The Plot Thickens: Creating a Histogram \\ Fat and Skinny Frequency Distributions \\ Excellent Charts \\ Excellent Charts Part Deux: Making Charts Pretty \\ Other Cool Charts \\ Chapter 5: Ice Cream and Crime: Computing Correlation Coefficients \\ What Are Correlations All About? \\ Computing a Simple Correlation Coefficient \\ More Excel?Bunches of Correlations à la Excel \\ Using the Amazing Analysis ToolPak to Compute Correlations \\ Understanding What the Correlation Coefficient Means \\ As More Ice Cream Is Eaten... the Crime Rate Goes Up (or Association Versus Causality) \\ Other Cool Correlations \\ Chapter 6: Just the Truth: An Introduction to Understanding Reliability and Validity \\ An Introduction to Reliability and Validity \\ All About Measurement Scales \\ Reliability?Doing It Again Until You Get It Right \\ Validity?Whoa! What Is the Truth? \\ A Last, Friendly Word \\ Validity and Reliability: Really Close Cousins \\ Part III: Taking Chances for Fun and Profit \\ Chapter 7: Hypotheticals and You: Testing Your Questions \\ So You Want to Be a Scientist... \\ The Null Hypothesis \\ The Research Hypothesis \\ What Makes a Good Hypothesis? \\ Chapter 8: Are Your Curves Normal? Probability and Why It Counts \\ Why Probability? \\ The Normal Curve (aka the Bell-Shaped Curve) \\ Our Favorite Standard Score: The z Score \\ Part IV: Significantly Different: Using Inferential Statistics \\ Chapter 9: Significantly Significant: What It Means for You and Me \\ The Concept of Significance \\ Significance Versus Meaningfulness \\ An Introduction to Inferential Statistics \\ An Introduction to Tests of Significance \\ An Introduction to Tests of Significance \\ Chapter 10: Only the Lonely: The One-Sample Z-Test \\ Introduction to the One-Sample Z-Test \\ Computing the Test Statistic \\ Using the Excel Z.TEST Function to Compute the z Value \\ Chapter 11: t(ea) for Two: Tests Between the Means of Different Groups \\ Introduction to the t-Test for Independent Samples \\ Computing the Test Statistic \\ Using the Amazing Analysis ToolPak to Compute the t Value \\ Special Effects: Are Those Differences for Real? \\ Chapter 12: t(ea) for Two (Again): Tests Between the Means of Related Groups \\ Introduction to the t-Test for Dependent Samples \\ Computing the Test Statistic \\ Using the Amazing Analysis ToolPak to Compute the t Value \\ Chapter 13: Two Groups Too Many? Try Analysis of Variance \\ Introduction to Analysis of Variance \\ Computing the F-Test Statistic \\ Using the Amazing Analysis ToolPak to Compute the F Value \\ Chapter 14: Two Too Many Factors: Factorial Analysis of Variance?A Brief Introduction \\ Introduction to Factorial Analysis of Variance \\ The Main Event: Main Effects in Factorial ANOVA \\ Even More Interesting: Interaction Effects \\ Computing the ANOVA F Statistic Using the Amazing Analysis ToolPak \\ Chapter 15: Cousins or Just Good Friends? Testing Relationships Using the Correlation Coefficient \\ Introduction to Testing the Correlation Coefficient \\ Computing the Test Statistic \\ Chapter 16: Predicting Who?ll Win the Super Bowl: Using Linear Regression \\ What Is Prediction All About? \\ The Logic of Prediction \\ Drawing the World?s Best Line (for Your Data) \\ Computing the Regression Equation Using the Amazing Analysis ToolPak \\ How Good Is Our Prediction? \\ The More Predictors, the Better? Maybe \\ Chapter 17: What to Do When You?re Not Normal: Chi-Square and Some Other Nonparametric Tests \\ Introduction to Nonparametric Statistics \\ Introduction to One-Sample Chi-Square \\ Computing the Chi-Square Test Statistic \\ Other Nonparametric Tests You Should Know About \\ Chapter 18: Some Other (Important) Statistical Procedures You Should Know About \\ Post Hoc Comparisons \\ Multivariate Analysis of Variance \\ Repeated Measures Analysis of Variance \\ Analysis of Covariance \\ Multiple Regression \\ Logistic Regression \\ Factor Analysis \\ Data Mining \\ Path Analysis \\ Structural Equation Modeling \\ Chapter 19: A Statistical Software Sampler \\ Selecting the Perfect Statistics Software \\ What?s Out There \\ Chapter 20: (Mini) Data Mining: A Introduction to Getting The Most Out Of Your BIG Data \\ Part V: Ten Things You?ll Want to Know and Remember \\ Chapter 21: The Ten (or More) Best (and Most Fun) Internet Sites for Statistics Stuff \\ How About Studying Statistics in Stockholm? \\ Calculators Galore! \\ Who?s Who and What?s Happened \\ It?s All Here \\ HyperStat \\ Data? You Want Data? \\ More and More Resources \\ Plain, But Fun \\ Online Statistical Teaching Materials \\ And, of Course, YouTube... \\ Chapter 22: The Ten Commandments of Data Collection \\ Appendix A: Excel-erate Your Learning: All You Need to Know About Excel \\ Appendix B: Tables \\ Appendix C: Data Sets \\ Appendix D: Answers to Practice Questions \\ Appendix E: Math ? Just the Basics \\ Appendix F: The Reward: The Brownie Recipe
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