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Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel 5th ed. [Minkštas viršelis]

4.20/5 (36 ratings by Goodreads)
(University of Kansas, USA),
  • Formatas: Paperback / softback, 512 pages, aukštis x plotis x storis: 251x175x18 mm, weight: 794 g, Illustrations
  • Išleidimo metai: 14-May-2021
  • Leidėjas: SAGE Publications Inc
  • ISBN-10: 1071803883
  • ISBN-13: 9781071803882
Kitos knygos pagal šią temą:
Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel 5th ed.Didesnis paveikslėlis
  • Formatas: Paperback / softback, 512 pages, aukštis x plotis x storis: 251x175x18 mm, weight: 794 g, Illustrations
  • Išleidimo metai: 14-May-2021
  • Leidėjas: SAGE Publications Inc
  • ISBN-10: 1071803883
  • ISBN-13: 9781071803882
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9781071803882.html
Raktažodžiai:
"This Microsoft Excel version of this bestelling text presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Students appreciate the book's unhurried pace and thorough, friendly presentation using a step-by-step approach to explaining each statistic and its procedure in Excel. Opening with an introduction to Excel, including coverage of how to use functions and formulas, this text shows students how to install and use the Excel Data Analysis Tools optionto access a host of useful analytical techniques. The book walks readers through various statistical procedures, beginning with simple descriptive statistics, correlations, and graphical representations of data, and ending with inferential techniques, analysis of variance, and a final chapter on working with large datasets and data mining using Excel. New to the Fifth Edition is new co-author Bruce Frey who has added a new feature on statisticians throughout history (with a focus on the contributions of women and people of color). He has updated the "Real-World Stats" feature, and added more on effect sizes, updated the discussions on hypotheses, measurement concepts like validity and reliability, and has more closely tied analytical choices to the levelof measurement of variables. A website is available for the book with resources for instructors and students"--

This Fifth Edition of Neil J. Salkind’s Statistics for People Who (Think They) Hate Statistics: Using Microsoft Excel, presents an often intimidating and difficult subject in a way that is clear, informative, and personable. Opening with an introduction to Excel, including coverage of how to use functions and formulas, this edition shows students how to install the Excel Data Analysis Tools option to access a host of useful analytical techniques. New to the Fifth Edition is new co-author Bruce Frey who has added a new feature on statisticians throughout history (with a focus on the contributions of women and people of color). He has updated the "Real-World Stats” feature, and added more on effect sizes, updated the discussions on hypotheses, measurement concepts like validity and reliability, and has more closely tied analytical choices to the level of measurement of variables.
Preface xvi
Acknowledgments xviii
And Now, About the Fifth Edition... xix
About the Authors xxi
PART I YIPPEE! I'M IN STATISTICS!
1(42)
Chapter 1 Statistics or Sadistics? It's Up to You
4(14)
Why Statistics?
4(2)
And Why Excel?
5(1)
A 5-Minute History of Statistics
6(2)
People Who Loved Statistics: Blaise Pascal
7(1)
Statistics: What It Is (and Isn't)
8(3)
What Are Descriptive Statistics?
8(1)
What Are Inferential Statistics?
9(1)
In Other Words
10(1)
Tooling Around With the Data Analysis Tools
11(1)
What Am I Doing in a Statistics Class?
12(1)
Ten Ways to Use This Book (and Learn Statistics at the Same Time!)
13(2)
About the Book's Features
15(1)
Key to Difficulty Icons
16(1)
Key to "How Much Excel" Icons
16(1)
Glossary
17(1)
Summary
17(1)
Chapter 2 Getting Started in Excel
18(25)
What's a Formula?
19(3)
Creating a Formula
19(2)
Operator, Operator--Get Me a Formula!
21(1)
Beware the Parentheses
21(1)
What's a Function?
22(12)
Using a Function
23(1)
Inserting a Function (When You Know the Function's Name and How It Works)
24(1)
Inserting a Function Using the Insert Function (fx) Command
25(2)
Inserting a Function Using Formulas → More Functions → Statistical
27(1)
Using Functions in Formulas
28(1)
We're Taking Names: Naming Ranges
29(2)
Using Ranges
31(3)
Real-World Stats
34(1)
All You Need to Know About Using the Amazing Data Analysis Tools
34(1)
Choosing the Right Tool for the Job
35(2)
Don't Have It? (Installation Again!)
37(1)
A Mac Alternative to the Data Analysis Tools
37(4)
Getting Started with StatPlus
38(1)
Computing Descriptive Statistics
38(2)
Options and Preferences
40(1)
What StatPlus Can Do
40(1)
Time to Practice
41(2)
PART II SIGMA FREUD AND DESCRIPTIVE STATISTICS
43(2)
Chapter 3 Computing and Understanding Averages: Means to an End
45(1)
Computing the Mean
46(1)
And Now Using Excel's AVERAGE Function
47(3)
Computing a Weighted Mean
50(2)
Computing the Median
52(4)
And Now Using Excel's MEDIAN Function
53(3)
Computing the Mode
56(5)
And Now Using Excel's MODE.SNGL Function
57(2)
Apple Pie a la Bimodal
59(1)
And Now Using Excel's MODE.MULT Function
59(2)
Using the Amazing Data Analysis Tools to Compute Descriptive Statistics
61(4)
Make the Data Analysis Tools Output Pretty
64(1)
Click or Drag?
65(1)
When to Use What Measure of Central Tendency (and All You Need to Know About Scales of Measurement for Now)
65(4)
A Rose by Any Other Name: The Nominal Level of Measurement
66(1)
Any Order Is Fine With Me: The Ordinal Level of Measurement
66(1)
1 + 1=2: The Interval Level of Measurement
66(1)
Can Anyone Have Nothing of Anything? The Ratio Level of Measurement
66(1)
In Sum
67(1)
Real-World Stats
68(1)
Summary
69(1)
Time to Practice
69(2)
Chapter 4 Understanding Variability: Vive la Difference
71(17)
Why Understanding Variability Is Important
71(2)
Computing the Range
73(1)
Computing the Standard Deviation
74(7)
And Now Using Excel's STDEV.S Function
76(3)
Why n-1? What's Wrong With Just n?
79(1)
What's the Big Deal?
80(1)
Computing the Variance
81(2)
And Now Using Excel's VAR.S Function
82(1)
STDEV.S Is to STDEV.P as VAR.S Is to VAR.P
83(2)
People Who Loved Statistics: Florence Nightingale
84(1)
The Standard Deviation Versus the Variance
84(1)
Using the Amazing Data Analysis Tools (Again!)
85(1)
Real-World Stats
85(1)
Summary
86(1)
Time to Practice
86(2)
Chapter 5 Creating Graphs: A Picture Really Is Worth a Thousand Words
88(31)
Why Illustrate Data?
88(1)
Ten Ways to a Great Figure (Eat Less and Exercise More?)
89(1)
First Things First: Creating a Frequency Distribution
90(3)
People Who Loved Statistics: Helen M. Walker
91(1)
The Classiest of Intervals
91(2)
The Plot Thickens: Creating a Histogram
93(9)
The Tally-Ho Method
95(1)
Using the Amazing Data Analysis Tools to Create a Histogram
96(4)
The Next Step: A Frequency Polygon
100(1)
Cumulating Frequencies
101(1)
Fat and Skinny Frequency Distributions
102(5)
Average Value
103(1)
Variability
103(1)
Skewness
104(1)
Kurtosis
105(2)
Excel-lent Charts
107(3)
Your First Excel Chart: A Moment to Remember (Sigh)
108(2)
Excel-lent Charts Part Deux: Making Charts Pretty
110(1)
Working with Chart Elements
111(4)
Other Cool Charts
115(2)
Bar Charts
115(1)
Line Charts
115(1)
Pie Charts
116(1)
Real-World Stats
117(1)
Summary
117(1)
Time to Practice
118(1)
Chapter 6 Computing Correlation Coefficients: Ice Cream and Crime
119(26)
What Are Correlations All About?
119(4)
Types of Correlation Coefficients: Flavor 1and Flavor 2
120(3)
Computing a Simple Correlation Coefficient
123(9)
And Now Using Excel's CORREL Function
125(1)
A Visual Picture of a Correlation: The Scatterplot
126(4)
Using Excel to Create a Scatterplot
130(1)
Bunches of Correlations: The Correlation Matrix
131(1)
More Excel: Bunches of Correlations a la Excel
132(1)
Using the Amazing Data Analysis Tools to Compute Correlations
132(3)
Understanding What the Correlation Coefficient Means
135(3)
Using-Your-Thumb Rule
135(1)
Special Effects! Correlation Coefficient
136(1)
A Determined Effort: Squaring the Correlation Coefficient
136(2)
As More Ice Cream Is Eaten, the Crime Rate Goes Up (or Association Versus Causality)
138(1)
Other Cool Correlations
139(1)
Real-World Stats
140(1)
Summary
140(1)
Time to Practice
141(4)
Chapter 7 Understanding Reliability and Validity: Just the Truth
145(20)
An Introduction to Reliability and Validity
145(2)
What's Up With This Measurement Stuff?
146(1)
Reliability: Doing It Again Until You Get It Right
147(2)
Test Scores: Truth or Dare
147(1)
Observed Score = True Score + Error Score
148(1)
Different Types of Reliability
149(7)
Test-Retest Reliability
149(1)
Parallel Forms Reliability
150(1)
People Who Loved Statistics: Euphemia Lofton Haynes
151(1)
Internal Consistency Reliability
152(3)
Interrater Reliability
155(1)
How Big Is Big? Finally: Interpreting Reliability Coefficients
156(2)
And If You Can't Establish Validity Then What?
157(1)
Just One More Thing
157(1)
Validity: Whoa! What Is the Truth?
158(3)
Different Types of Validity
158(1)
Content-Based Validity
159(1)
Criterion-Based Validity
159(1)
Construct-Based Validity
160(1)
And If You Can't Establish Validity Then What?
161(1)
A Last Friendly Word
161(1)
Validity and Reliability: Really Close Cousins
162(1)
Real-World Stats
163(1)
Summary
163(1)
Time to Practice
164(1)
PART III TAKING CHANCES FOR FUN AND PROFIT
165(36)
Chapter 8 Hypotheticals and You: Testing Your Questions
167(14)
So You Want to Be a Scientist
167(1)
Samples and Populations
168(1)
The Null Hypothesis
169(2)
The Purposes of the Null Hypothesis
170(1)
The Research Hypothesis
171(5)
The Nondirectional Research Hypothesis
172(1)
The Directional Research Hypothesis
173(3)
Some Differences Between the Null Hypothesis and the Research Hypothesis
176(1)
What Makes a Good Hypothesis?
176(3)
Real-World Stats
178(1)
Summary
179(1)
Time to Practice
179(2)
Chapter 9 Probability and Why It Counts: Fun With a Bell-Shaped Curve
181(20)
Why Probability?
181(1)
The Normal Curve (a.k.a. the Bell-Shaped Curve)
182(5)
Hey, That's Not Normal!
183(3)
More Normal Curve 101
186(1)
Our Favorite Standard Score: The z Score
187(12)
People Who Love Statistics: Dionne L. Price
190(1)
What z Scores Represent
191(2)
What z Scores Really Represent
193(2)
Hypothesis Testing and z Scores: The First Step
195(1)
Using Excel to Compute z Scores
196(2)
Real-World Stats
198(1)
Summary
199(1)
Time to Practice
199(2)
PART IV SIGNIFICANTLY DIFFERENT: USING INFERENTIAL STATISTICS
201(136)
Chapter 10 Significantly Significant: What It Means for You and Me
203(19)
The Concept of Significance
203(5)
If Only We Were Perfect
206(1)
The World's Most Important Table (for This Semester Only)
206(2)
Back to Type I Errors
208(1)
Significance Versus Meaningfulness
208(4)
Statistical Versus Practical Significance
210(2)
An Introduction to Inferential Statistics
212(3)
How Inference Works
212(1)
How to Select What Test to Use
213(1)
Here's How to Use the Chart
213(2)
An Introduction to Tests of Significance
215(3)
Tests of Significance
215(1)
How a Test of Significance Works: The Plan
215(2)
Here's the Picture That's Worth a Thousand Words
217(1)
Confidence Intervals--Be Even More Confident
218(2)
People Who Loved Statistics
219(1)
Real-World Stats
220(1)
Summary
220(1)
Time to Practice
220(2)
Chapter 11 The One-Sample Z Test: Only the Lonely
222(14)
Introduction to the One-Sample Z Test
222(3)
The Path to Wisdom and Knowledge
223(2)
Computing the Z Test Statistic
225(3)
Time for an Example
226(2)
So How Do I Interpret z = 2.38, p > 05?
228(1)
Using the Excel Z.TEST Function to Compute the z Value
228(2)
Special Effects: Are Those Differences for Real?
230(3)
Understanding Effect Size
232(1)
Real-World Stats
233(1)
Summary
233(1)
Time to Practice
233(3)
Chapter 12 t(ea) for Two: Tests Between the Means of Different Groups
236(17)
Introduction to the f Test for Independent Samples
236(1)
The Path to Wisdom and Knowledge
237(2)
Computing the f Test Statistic
239(1)
Time for an Example
240(3)
So How Do I Interpret tm = - O.K. p < 05?
243(1)
The Effect Size and f(ea) for Two
243(1)
Computing and Understanding the Effect Size
244(2)
Two Very Cool Effect Size Calculators
245(1)
And Now... Using Excel's T.TEST Function
246(2)
Using the Amazing Data Analysis Tools to Compute the t Value
248(2)
Results
250(1)
Real-World Stats
251(1)
Summary
251(1)
Time to Practice
252(1)
Chapter 13 t(ea) for Two (Again): Tests Between the Means of Related Groups
253(1)
Introduction to the t Test for Dependent Samples
253(3)
The Path to Wisdom and Knowledge
256(1)
Computing the t Test Statistic
256(3)
So How Do I Interpret t[ 24] = 2.65, p > 05?
259(1)
And Now... Using Excel's T.TEST Function
259(3)
Using the Amazing Data Analysis Tools to Compute the t Value
262(3)
The Effect Size for f(ea) for Two (Again)
265(1)
Real-World Stats
265(1)
Summary
266(1)
Time to Practice
266(3)
Chapter 14 Analysis of Variance: Two Groups Too Many?
269(1)
Introduction to Analysis of Variance
269(1)
The Path to Wisdom and Knowledge
270(2)
Different Flavors of ANOVA
272(1)
Computing the FTest Statistic
273(7)
So How Do I Interpret F(2,27) = 8.80, p > 05?
279(1)
Time for an Example
279(1)
And Now Using Excel's F.DIST and F.TEST Functions
280(1)
Using the Amazing Data Analysis Tools to Compute the F Value
280(3)
The Effect Size for One-Way ANOVA
283(1)
Real-World Stats
284(1)
Summary
284(1)
Time to Practice
285(2)
Chapter 15 Factorial Analysis of Variance: Two Too Many Factors
287(1)
Introduction to Factorial Analysis of Variance
287(1)
Two Flavors of Factorial ANOVA
288(1)
The Path to Wisdom and Knowledge
289(2)
A New Flavor of ANOVA
291(1)
Factorial ANOVA
291(1)
The Main Event: Main Effects in Factorial ANOVA
292(1)
Even More Interesting: Interaction Effects
293(2)
People Who Loved Statistics: Gertrude Mary Cox
295(1)
Using the Amazing Data Analysis Tools to Compute the ANOVA F Statistic
295(5)
Computing the Effect Size for Factorial ANOVA
300(1)
Real-World Stats
301(1)
Summary
301(1)
Time to Practice
301(2)
Chapter 16 Testing Relationships Using the Correlation Coefficient: Cousins or Just Good Friends?
303(1)
Introduction to Testing the Correlation Coefficient
303(3)
The Path to Wisdom and Knowledge
306(1)
Computing the Test Statistic
306(6)
So How Do I Interpret r(28) = .393, p > 05?
309(1)
Causes and Associations (Again!)
310(1)
Significance Versus Meaningfulness (Again, Again!)
311(1)
Real-World Stats
311(1)
Summary
312(1)
Time to Practice
312(1)
Chapter 17 Using Linear Regression: Predicting the Future
313(1)
Introduction to Linear Regression
313(1)
What Is Prediction All About?
314(1)
The Logic of Prediction
315(4)
Drawing the World's Best Line [ For Your Data)
319(3)
And Now... Using Excel's SLOPE Function
322(3)
And Now... Using Excel's INTERCEPT Function
325(2)
Using the Amazing Data Analysis Tools to Compute the Regression Equation
327(2)
How Good Is Our Prediction?
329(1)
The More Predictors, the Better? Maybe
330(1)
The Big Rule When It Comes to Using Multiple Predictor Variables
331(1)
Real-World Stats
332(1)
Summary
333(1)
Time to Practice
333(4)
PART V MORE STATISTICS! MORE TOOLS! MORE FUN!
337(1)
Chapter 18 Chi-Square and Some Other Nonparametric Tests: What to Do When You're Not Normal
337(12)
Introduction to Nonparametric Statistics
337(1)
Introduction to the Goodness-of-Fit (One-Sample) Chi-Square
338(1)
Computing the Goodness-of-Fit Chi-Square Test Statistic
339(3)
So How Do I Interpret Χ2 = 20.6, p > 05?
342(1)
And Now Using Excel's CHISQ.TEST Function
343(2)
Chi-Square Test of Independence
345(1)
Other Nonparametric Tests You Should Know About
346(1)
Real-World Stats
347(1)
Summary
347(1)
Time to Practice
348(1)
Chapter 19 Some Other (Important) Statistical Procedures You Should Know About
349(1)
Multivariate Analysis of Variance
350(1)
Repeated Measures Analysis of Variance
350(1)
Analysis of Covariance
351(1)
Multiple Regression
351(1)
Meta-Analysis
352(1)
Discriminant Analysis
353(1)
Factor Analysis
354(1)
Path Analysis
355(1)
Structural Equation Modeling
355(1)
Summary
356(1)
Chapter 20 Data Mining: An Introduction to Getting the Most Out of Your BIG Data
357(2)
Our Sample Data Set--Who Doesn't Love Babies?
359(1)
Some Excel Data-Exploring Functions
360(1)
The DAVERAGE Function
360(1)
What DAVERAGE Does
360(1)
What DAVERAGE Looks Like
360(1)
Using the DAVERAGE Function
361(2)
The COUNTIF Function
363(1)
What COUNTIF Does
363(1)
What COUNTIF Looks Like
363(1)
Using the COUNTIF Function
363(1)
Pivot Tables and Cross-Tabulation: Finding Hidden Patterns
364(1)
Creating a Pivot Table
365(2)
Modifying a Pivot Table
367(1)
Summary
368(1)
Time to Practice
368(1)
Appendices: Information Never Ends
369(1)
Appendix A Excel-erate Your Learning: All You Need to Know About Excel
370(6)
Appendix B Tables
376(16)
Appendix C Data Sets
392(26)
Appendix D Answers to Practice Questions
418(33)
Appendix E Math: Just the Basics
451(5)
Appendix F A Statistical Software Sampler
456(8)
Appendix G The 10 (or More) Best (and Most Fun) Internet Sites for Statistics Stuff
464(4)
Appendix H The 10 Commandments of Data Collection
468(3)
Appendix I The Reward: The Brownie Recipe
471(2)
Glossary 473(4)
Index 477