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

by Salkind, Neil

• ISBN13: 9781412924825
• ISBN10: 1412924820
• Format: Paperback
• Copyright: 2006-07-14
• Publisher: Sage Publications, Inc

Summary

Derived from his bestselling text Statistics for People Who (Think They) Hate Statistics , author Neil J. Salkind presents readers with The Excel Edition ! Using the same personable and clear style that made previous editions so successful, this new edition teaches students how they can use Excel to learn the basics of statistics. This is not a text on how to use Excel, rather it illustrates how this program can make the statistics learning experience a better one. Key Features: Applies Excel to statistical techniques: Introductory chapters present Excel as an accessible tool for statistical analyses. Students are shown how to install the free Excel Analysis ToolPak to earn access to a host of new and very useful analytical techniques such as ANOVA, Correlation, Covariance, Moving Averages, Regression, and more. In addition, other Excel formulae illustrate reliability, goodness-of-fit, and Chi-square. Offers an unhurried pace and thorough presentation: Using a non-intimidating, user-friendly style, this book walks students through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. Real-world examples from a variety of settings illustrate the utility of statistics and reinforce concepts introduced. Provides valuable teaching tools: Pedagogical features help present an often intimidating and difficult subject in a way that is informative, engaging, and clear. These tools include icons, tip boxes, further readings, a glossary, the famous "Difficulty Rating Scale" and "Top Ten" lists, and much more! In addition, an extensive Excel functionality is located at the back of the book. Instructor's Resources! Instructor Resources on CD are available to qualified adopters of The Excel Edition. These resources include sample syllabi, data sets, chapter overviews and objectives, chapter outlines, PowerPoint slides, discussion questions and class activities, additional resources, test items per chapter, and much more! Intended Audience: This is an excellent textbook for undergraduate and graduate students studying statistics in courses such as Introduction to Statistics, Statistics Using Excel, Data Analysis, and Research Methods. It is ideal for courses in which Excel is the primary statistical package discussed.

Table of Contents

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)
About Those Icons	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	108	(2)
Ice Cream and Crime: Computing Correlation Coefficients	110	(25)
What Are Correlations All About?	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
More About Table 8.1	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
Answers to Practice Questions	268	(2)
Predicting Who'll Win the Super Bowl: Using Linear Regression	270	(19)
What Is Prediction All About?	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)
Answers to Practice Questions	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)
Answers to Practice Questions	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)
All About Measurement Scales	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)
Answers to Practice Questions	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)
About the Author	403