# Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics, Safari, 2nd Edition

Published Date: Aug 17, 2009

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## Description

Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statisticsi s a practical, up-to-date introduction to statistics—for everyone! Thought you couldn’t learn statistics? You can—and you will! One easy step at a time, this fully updated book teaches you all the statistical techniques you’ll need for finance, quality, marketing, the social sciences, or anything else! Simple jargon-free explanations help you understand every technique. Practical examples and worked-out problems give you hands-on practice. Special sections present detailed instructions for developing statistical answers, using spreadsheet programs or any TI-83/TI-84 compatible calculator. This edition delivers new examples, more detailed problems and sample solutions, plus an all-new chapter on powerful multiple regression techniques. Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional “Equation Blackboard” sections reveal the mathematical foundations of statistics right before your eyes! You’ll learn how to:

• Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3

• Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics

• Use probability and probability distributions

• Work with sampling distributions and confidence intervals

• Test hypotheses with Z, t, chi-square, ANOVA, and other techniques

• Perform powerful regression analysis and modeling

• Use multiple regression to develop models that contain several independent variables

• Master specific statistical techniques for quality and Six Sigma programs

Acknowledgments     viii
Introduction: The Even You Can Learn Statistics Owners Manual     xi
Chapter 1 Fundamentals of Statistics      1
1.1 The First Three Words of Statistics     2
1.2 The Fourth and Fifth Words      4
1.3 The Branches of Statistics      5
1.4 Sources of Data      6
1.5 Sampling Concepts      7
1.6 Sample Selection Methods     9
Chapter 2 Presenting Data in Charts and Tables     19
2.1 Presenting Categorical Variables     19
2.2 Presenting Numerical Variables     26
2.3 Misusing Charts     32
Chapter 3 Descriptive Statistics      43
3.1 Measures of Central Tendency      43
3.2 Measures of Position     47
3.3 Measures of Variation     51
3.4 Shape of Distributions      57
Chapter 4 Probability      71
4.1 Events    71
4.2 More Definitions      72
4.3 Some Rules of Probability      74
4.4 Assigning Probabilities      77
Chapter 5 Probability Distributions      83
5.1 Probability Distributions for Discrete Variables      83
5.2 The Binomial and Poisson Probability Distributions     89
5.3 Continuous Probability Distributions and the Normal Distribution      97
5.4 The Normal Probability Plot     105
Chapter 6 Sampling Distributions and Confidence Intervals      119
6.1 Sampling Distributions     119
6.2 Sampling Error and Confidence Intervals     123
6.3 Confidence Interval Estimate for the Mean Using the t Distribution (ó Unknown)      127
6.4 Confidence Interval Estimation for Categorical Variables      131
Chapter 7 Fundamentals of Hypothesis Testing      141
7.1 The Null and Alternative Hypotheses     141
7.2 Hypothesis Testing Issues      143
7.3 Decision-Making Risks     145
7.4 Performing Hypothesis Testing      147
7.5 Types of Hypothesis Tests      148
Chapter 8 Hypothesis Testing: Z and t Tests      153
8.1 Testing for the Difference Between Two Proportions     53
8.2 Testing for the Difference Between the Means of Two Independent Groups      160
8.3 The Paired t Test      166
Chapter 9 Hypothesis Testing: Chi-Square Tests and the One-Way Analysis of Variance (ANOVA)     179
9.1 Chi-Square Test for Two-Way Cross-Classification Tables      179
9.2 One-Way Analysis of Variance (ANOVA): Testing for the Differences Among the Means of More Than Two Groups      186
Chapter 10 Simple Linear Regression      207
10.1 Basics of Regression Analysis      208
10.2 Determining the Simple Linear Regression Equation     209
10.3 Measures of Variation      217
10.4 Regression Assumptions          222
10.5 Residual Analysis     223
10.6 Inferences About the Slope     225
10.7 Common Mistakes Using Regression Analysis      228
Chapter 11 Multiple Regression     245
11.1 The Multiple Regression Model      245
11.2 Coefficient of Multiple Determination     248
11.3 The Overall F test     249
11.4 Residual Analysis for the Multiple Regression Model      250
11.5 Inferences Concerning the Population Regression Coefficients      251
Chapter 12 Quality and Six Sigma Applications of Statistics      265
12.1 Total Quality Management      265
12.2 Six Sigma     267
12.3 Control Charts      268
12.4 The p Chart     271
12.5 The Parable of the Red Bead Experiment: Understanding Process Variability     276
12.6 Variables Control Charts for the Mean and Range      278
Appendix A Calculator and Spreadsheet Operation and Configuration      295
A.C1 Calculator Operation Conventions      295
A.C2 Calculator Technical Configuration      297
A.C3 Using the A2MULREG Program      298
A.C4 Using TI Connect      298
Appendix B Review of Arithmetic and Algebra     301
Assessment Quiz      301
Symbols     304
Appendix C Statistical Tables      311