# Statistics for People Who (Think They) Hate Statistics; The Excel Edition

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## 1412924820

• Format: Paperback
• Publisher: Sage Publications, Inc
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### Summary

A Note to the Student Why I Wrote this Book xvi
Acknowledgments xviii
 PART I Yippee! I'm in Statistics
1(38)
 Statistics or Sadistics? It's Up to You
5(14)
 Why Statistics?
5(1)
 And Why Excel?
6(1)
 A Five-Minute History of Statistics
6(2)
 Statistics: What It Is (and Isn't)
8(3)
 What Are Descriptive Statistics?
9(1)
 What Are Inferential Statistics?
9(1)
 In Other Words . . .
10(1)
 Tooling Around With the Analysis ToolPak
11(1)
 What Am I Doing in a Statistics Class?
11(2)
 Ten Ways to Use This Book (and Learn Statistics at the Same Time!)
13(2)
15(1)
 Key to Difficulty Icons
16(1)
 Key to ``How Much Excel'' Icons
17(1)
 Glossary
17(2)
 Summary
17(1)
 Time to Practice
17(2)
 All You Need to Know About Formulas and Functions
19(16)
 What's a Formula?
19(4)
 Creating a Formula
20(2)
 Operator, Operator---Get Me a Formula!
22(1)
 Beware the Parentheses
22(1)
 What's a Function?
23(12)
 Using a Function
24(5)
 Using Functions in Formulas
29(1)
 We're Taking Names: Naming Ranges
30(1)
 Using Ranges
31(1)
 Summary
32(1)
 Time to Practice
32(1)
33(2)
 All You Need to Know About Using the Amazing Data Analysis ToolPak
35(4)
 A Look at a Data Analysis Tool
36(1)
 Don't Have It?
37(2)
 PART II Σigma Freud and Descriptive Statistics
39(96)
 Computing and Understanding Averages: Means to an End
41(25)
 Computing the Mean
42(3)
 And Now . . . Using Excel's Average Function
43(2)
 Things to Remember
45(3)
 Computing a Weighted Mean
46(2)
 Computing the Median
48(5)
 And Now . . . Using Excel's Median Function
50(3)
 Things to Remember
53(1)
 Computing the Mode
53(3)
 And Now . . . Using Excel's Mode Function
54(2)
 Apple Pie a la Bimodal
56(1)
 Using the Amazing Analysis ToolPak to Compute Descriptive Statistics
56(5)
 Make the Analysis ToolPak Output Pretty
60(1)
 When to Use What
61(5)
 Summary
62(1)
 Time to Practice
62(1)
63(3)
 Vive la Difference: Understanding Variability
66(16)
 Why Understanding Variability Is Important
66(1)
 Computing the Range
67(1)
 Computing the Standard Deviation
68(7)
 And Now . . . Using Excel's STDEV Function
70(3)
 Why n -- I? What's Wrong With Just n?
73(1)
 What's the Big Deal?
74(1)
 Things to Remember
75(1)
 Computing the Variance
75(3)
 And Now . . . Using Excel's VAR Function
76(1)
 The Standard Deviation Versus the Variance
77(1)
 Using the Amazing Analysis ToolPak (AGAIN!)
78(4)
 Summary
78(1)
 Time to Practice
78(1)
79(3)
 A Picture Really Is Worth a Thousand Words
82(28)
 Why Illustrate Data?
82(1)
 Ten Ways to a Great Figure (Eat Less and Exercise More?)
83(1)
 First Things First: Creating a Frequency Distribution
84(2)
 The Classiest of Intervals
85(1)
 The Plot Thickens: Creating a Histogram
86(10)
 The Tally-Ho Method
88(1)
 Using the Amazing Analysis ToolPak to Create a Histogram
89(5)
 The Next Step: A Frequency Polygon
94(1)
 Cumulating Frequencies
94(2)
 Fat and Skinny Frequency Distributions
96(4)
 Average Value
96(1)
 Variability
96(1)
 Skewness
97(1)
 Kurtosis
98(2)
 Excellent Charts
100(4)
 Your First Excel Chart: A Moment to Remember
101(3)
 Excellent Charts Part Deux: Making Charts Pretty
104(1)
 Other Cool Charts
105(5)
 Bar Charts
106(1)
 Lines Charts
106(1)
 Pie Charts
107(1)
 Summary
107(1)
 Time to Practice
108(1)
108(2)
 Ice Cream and Crime: Computing Correlation Coefficients
110(25)
110(2)
 Types of Correlation Coefficients: Flavor 1 and Flavor 2
111(1)
 Things to Remember
112(2)
 Computing a Simple Correlation Coefficient
114(9)
 And Now . . . Using Excel's Correl Function
116(1)
 A Visual Picture of a Correlation: The Scatterplot
117(4)
 Using Excel to Create a Scatterplot
121(1)
 Bunches of Correlations: The Correlation Matrix
122(1)
 More Excel---Bunches of Correlations a la Excel
123(1)
 Using the Amazing Analysis ToolPak to Compute Correlations
124(2)
 Understanding What the Correlation Coefficient Means
126(3)
 Using-Your-Thumb Rule
126(1)
 A Determined Effort: Squaring the Correlation Coefficient
127(2)
 As More Ice Cream Is Eaten . . . the Crime Rate Goes Up (or Association Versus Causality)
129(1)
 Other Cool Correlations
130(5)
 Summary
131(1)
 Time to Practice
132(1)
133(2)
 PART III Taking Chances for Fun and Profit
135(38)
 Hypotheticals and You: Testing Your Questions
137(14)
 So You Want to Be a Scientist
137(2)
 Samples and Populations
138(1)
 The Null Hypothesis
139(2)
 The Purposes of the Null Hypothesis
140(1)
 The Research Hypothesis
141(5)
 The Nondirectional Research Hypothesis
142(1)
 The Directional Research Hypothesis
143(2)
 Some Differences Between the Null Hypothesis and the Research Hypothesis
145(1)
 What Makes a Good Hypothesis?
146(5)
 Summary
149(1)
 Time to Practice
149(1)
149(2)
 Are Your Curves Normal? Probability and Why It Counts
151(22)
 Why Probability?
151(1)
 The Normal Curve (a.k.a. the Bell-Shaped Curve)
152(7)
 Hey, That's Not Normal!
153(2)
 More Normal Curve 101
155(4)
 Our Favorite Standard Score: The z Score
159(14)
 Using Excel to Compute z Scores
161(3)
 What z Scores Represent
164(4)
 What z Scores Really Represent
168(1)
 Hypothesis Testing and z Scores: The First Step
169(1)
 Summary
170(1)
 Time to Practice
170(1)
171(2)
 PART IV Significantly Different: Using Inferential Statistics
173(164)
 Significantly Significant: What It Means for You and Me
175(17)
 The Concept of Significance
175(7)
 If Only We Were Perfect
176(2)
 The World's Most Important Table (for This Semester Only)
178(1)
179(1)
 Back to Type I Errors
180(2)
 Significance Versus Meaningfulness
182(2)
 An Introduction to Inferential Statistics
184(3)
 How Inference Works
184(1)
 How to Select What Test to Use
185(2)
 Here's How to Use the Chart
187(1)
 An Introduction to Tests of Significance
187(5)
 How a Test of Significance Works: The Plan
188(1)
 Here's the Picture That's Worth a Thousand Words
189(2)
 Summary
191(1)
 Time to Practice
191(1)
191(1)
 t(ea) for Two: Tests Between the Means of Different Groups
192(19)
 Introduction to the t Test for Independent Samples
192(3)
 The Path to Wisdom and Knowledge
193(2)
 Computing the Test Statistic
195(7)
 So How Do I Interpret t(58) = -.14, p > .05?
199(1)
 And Now . . . Using Excel's TTEST Function
200(2)
 Using the Amazing Data Analysis ToolPak to Compute the t Value
202(3)
 Special Effects: Are Those Differences for Real?
205(4)
 Computing and Understanding the Effect Size
206(2)
 A Very Cool Effect Size Calculator
208(1)
 Summary
209(1)
 Time to Practice
209(1)
209(2)
 t(ea) for Two (Again): Tests Between the Means of Related Groups
211(14)
 Introduction to the t Test for Dependent Samples
211(3)
 The Path to Wisdom and Knowledge
212(2)
 Computing the Test Statistic
214(6)
 So How Do I Interpret t(24) = 2.45, p < .05?
217(1)
 And Now . . . Using Excel's TTEST Function
218(2)
 Using the Amazing Data Analysis ToolPak to Compute the t Value
220(3)
 Summary
223(1)
 Time to Practice
223(1)
224(1)
 Two Groups Too Many? Try Analysis of Variance
225(19)
 Introduction to Analysis of Variance
225(4)
 The Path to Wisdom and Knowledge
226(1)
 Different Flavors of Anova
226(3)
 Computing the F Test Statistic
229(8)
 So How Do I Interpret F(2.27) = 8.80. p < .05?
236(1)
 And Now . . . Using Excel's FDIST and FTEST Functions
237(1)
 Using the Amazing Data Analysis ToolPak to Compute the F Value
237(7)
 Summary
240(1)
 Time to Practice
240(2)
242(2)
 Two Too Many Factors: Factorial Analysis of Variance: A Brief Introduction
244(15)
 Introduction to Factorial Analysis of Variance
244(5)
 Two Flavors of Factorial Anova
245(1)
 The Path to Wisdom and Knowledge
246(1)
 A New Flavor of Anova
247(2)
 The Main Event: Main Effects in Factorial Anova
249(2)
 Even More Interesting: Interaction Effects
251(2)
 Computing the Anova F Statistic Using the Amazing Data Analysis ToolPak
253(6)
 Summary
257(1)
 Time to Practice
257(1)
257(2)
 Cousins or Just Good Friends? Testing Relationships Using the Correlation Coefficient
259(11)
 Introduction to Testing the Correlation Coefficient
259(1)
 The Path to Wisdom and Knowledge
260(1)
 Computing the Test Statistic
260(10)
 So How Do I Interpret r(27) = .393, p < .05?
265(1)
 Causes and Associations (Again!)
266(1)
 Significance Versus Meaningfulness (Again, Again!)
267(1)
 Summary
267(1)
 Time to Practice
267(1)
268(2)
 Predicting Who'll Win the Super Bowl: Using Linear Regression
270(19)
270(1)
 The Logic of Prediction
271(4)
 Drawing the World's Best Line (for Your Data)
275(8)
 And Now . . . Using Excel's Slope Function
278(2)
 And Now . . . Using Excel's Intercept Function
280(3)
 How Good Is Our Prediction?
283(1)
 The More Predictors the Better? Maybe
284(5)
 The Big Rule When It Comes to Using Multiple Predictor Variables
285(1)
 Summary
286(1)
 Time to Practice
286(1)
287(2)
 What to Do When You're Not Normal: Chi-Square and Some Other Nonparametric Tests
289(11)
 Introduction to Nonparametric Statistics
289(1)
 Introduction to One-Sample Chi-Square
290(1)
 Computing the Chi-Square Test Statistic
291(5)
 So How Do I Interpret X 2 (2) = 20.6, P < .05?
295(1)
 And Now . . . Using Excel's CHIDIST Function
295(1)
 Other Nonparametric Tests You Should Know About
296(4)
 Summary
296(2)
 Time to Practice
298(1)
298(2)
 Just the Truth: An Introduction to Understanding Reliability and Validity
300(21)
 An Introduction to Reliability and Validity
300(2)
 What's Up With This Measurement Stuff?
301(1)
302(3)
 A Rose by Any Other Name: The Nominal Level of Measurement
303(1)
 Any Order Is Fine With Me: The Ordinal Level of Measurement
303(1)
 1 + 1 = 2: The Interval Level of Measurement
303(1)
 Can Anyone Have Nothing of Anything? The Ratio Level of Measurement
304(1)
 In Sum . . .
304(1)
 Reliability---Doing It Again Until You Get It Right
305(9)
 Tests Scores---Truth or Dare
305(1)
 Observed Score = True Score + Error Score
306(1)
 Different Types of Reliability
307(6)
 How Big Is Big? Interpreting Reliability Coefficients
313(1)
 Just One More Thing
314(1)
 Validity---Whoa! What Is the Truth?
314(5)
 Different Types of Validity
315(3)
 A Last, Friendly Word
318(1)
 Validity and Reliability: Really Close Cousins
319(2)
 Time to Practice
320(1)
320(1)
 Some Other (Important) Statistical Procedures You Should Know About
321(6)
 Multivariate Analysis of Variance
321(1)
 Repeated Measures Analysis of Variance
322(1)
 Analysis of Covariance
323(1)
 Multiple Regression
323(1)
 Factor Analysis
324(1)
 Path Analysis
325(1)
 Structural Equation Modeling
325(2)
 Summary
326(1)
 A Statistical Software Sampler
327(10)
 Selecting the Perfect Statistics Software
328(1)
 What's Out There
329(8)
 The Free Stuff
330(2)
 Time to Pay
332(3)
 Summary
335(2)
 PART V Ten Things You'll Want to Know and Remember
337(13)
 The Ten (or More) Best Internet Sites for Statistics Stuff
339(6)
 Tons and Tons of Resources
339(1)
 Calculators Galore!
340(1)
 Who's Who and What's Happened
341(1)
 It's All Here
341(1)
 HyperStat
341(1)
 Data? You Want Data?
342(1)
 More and More and More and More Resources
343(1)
 Plain, But Fun
343(1)
 How About Studying Statistics in Stockholm?
343(1)
 Online Statistical Teaching Materials
344(1)
 More and More and More Stuff
344(1)
 The Ten Commandments of Data Collection
345(5)
Appendix A: Excel-erate Your Learning: All You Need to Know About Excel 350(6)
Appendix B: Tables 356(15)
Appendix C: The Data Sets 371(9)
Glossary 380(11)
Index 391(12)