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

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ISBN-10: 1412924820

ISBN-13: 9781412924825

Edition: 2007

Authors: Neil J. Salkind

List price: $52.95
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Description:

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…    
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Book details

List price: $52.95
Copyright year: 2007
Publisher: SAGE Publications, Incorporated
Publication date: 7/14/2006
Binding: Paperback
Pages: 424
Size: 7.00" wide x 10.00" long x 0.90" tall
Weight: 1.562
Language: English

Neil J. Salkind received his PhD from the University of Maryland in Human Development. After teaching for 35 years at the University of Kansas, he remains a professor emeritus in the department of psychology and research in education, where he continues to collaborate with colleagues and work with students. His early interests were in the area of children's cognitive development, and after research in the areas of cognitive style and (what was then known as) hyperactivity, he was a postdoctoral fellow at the University of North Carolina's Bush Center for Child and Family Policy. His work then changed direction to focus on child and family policy, specifically the impact of alternative forms…    

A Note to the Student Why I Wrote this Book
Acknowledgments
Yippee! I'm in Statistics
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
Glossary
Summary
Time to Practice
All Your Need to Know About Formulas and Functions
What's a Formula?
What's a Function?
Summary
Time to Practice
Answers to Practice Questions
All You Need to Know About Using the Amazing Data Analysis Toolpak
A Look at a Data Analysis Tool
Don't Have It?
Sigma Freud and Descriptive Statistics
Computing and Understanding Averages: Means to an End
Computing the Mean
Things to Remember
Computing the Median
Things to Remember
Computing the Mode
Using the Amazing Analysis ToolPak to Compute Descriptive Statistics
When to Use What
Summary
Time to Prctice
Answers to Practice Questions
Vive la Diff�rence: Understanding Variability
Why Understading Variability Is Important
Computing the Range
Computing the Standard Deviation
Things to Remember
Computing the Variance
Using the Amazing Analysis ToolPak (AGAIN)
Summary
Time to Practice
Answers to Practice Questions
A Picture Really Is Worth a Thousand Words
Why Illustrate Data?
Ten Ways to a Great Figure (Eat Less and Exercise More?)
Fist 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
Summary
Time to Practice
Answers to Practice Questions
Ice Cream and Crime: Computing Correlation Coefficients
What Are Correlations All About?
Things to Remember
Computing a Simple Correlation Coefficient
More Excel--Bunches of Correlatios à la Excel
Using the Amazing Analysis ToolPak to Compute Corelations
Understanding What the Correlation Coefficient Means
As More Ice Cream Is Eaten ... the Crime Rate Goes Up (or Association Versus Causality)
Other Cool Correlations
Summary
Time to Practice
Answers to Practice Questions
Taking Chances for Fun and Profit
Hypotheticals and You: Testing Your Questions
So You Want to Be a Scientist ...
The Null Hypothesis
The Research Hypothesis
What Makes a Good Hypothesis?
Summary
Time to Practice
Answers to Practice Questions
Are Your Curves Normal? Probability and Why It Counts
Why Probability?
The Normal Curve (a.k.a. the Bell-Shaped Curve)
Our Favorite Standard Score: The z Score
Summary
Time to Practice
Answers to Practice Questions
Significantly Different: Using Inferential Statistics
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
Summary
Time to Practice
Answers to Practice Questions
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 Data Analysis ToolPak to Compte the t Value
Special Effects: Are Those Differences for Real?
Summary
Time to Practice
Answers to Practice Questions
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 Data Analysis ToolPak to Compute the t Value
Summary
Time to Practice
Answers to Practice Questions
Two Groups Too Many? Try Analysis of Variance
Introduction to Analysis of Variance
Computing the F Test Statistic
Using the Amazing Data Analysis ToolPak to Compute the F Value
Summary
Time to Practice
Answers to Practice Questions
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 Data Analysis ToolPak
Summary
Time to Practice
Answers to Practice Questions
Cousins or Just Good Friends? Testing Relationships Using the Correlation Coefficient
Introduction to Testing the Correlation Coefficient
Computing the Test Statistic
Summary
Time to Practice
Answers to Practice Questions
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)
How Good Is Our Prediction?
The More Predictors the Better? Maybe
Summary
Time to Practice
Answers to Practice Questions
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
Summary
Time to Practice
Answers to Practice Questions
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! Wat Is the Truth?
Validity and Reliability: Reallly Close Cousins
Time to Practice
Answers to Practice Questions
Some Other (Important) Statistical Procedures You Should Know About
Multivariate Analysis of Variance
Repeated Measures Analysis of Variance
Analysis of Covariance
Multiple Regression
Factor Analysis
Path Analysis
Structural Equation Modeling
Summary
A Statistical Software Sampler
Selecting the Perfect Statistics Software
What's Out There
Summary
Ten Things You'll Want to Know and Remember
The Ten (or More) Best Internet Sites for Statistics Stuff
Tons and Tons of Resources
Calculators Galore!
Who's Who and What's Happened
It's All Here
HyperStat
Data? You Want Data?
More and More and More and More Resources
Plain, But Fun
How About Studying Statistics in Stockholm?
Online Statistical Teaching Materials
More and More and More Stuff
The Ten Commandments of Data Collection
Excel-erate your Learning: All You Need to Know About Excel
Tables
The Data Sets
Glossary
Index
About the Author