Even You Can Learn Statistics

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Introduction. 1. Fundamentals of Statistics. The Five Basic Words
of Statistics. Population. Sample. Parameter. Statistic. Variable.
The Branches of Statistics. Descriptive Statistics. Inferential
Statistics. Sources of Data. Published Sources. Experiments.
Surveys. Sampling Concepts. Sampling. Probability Sampling. Simple
Random Sampling. Frame. Sample Selection Methods. Sampling with
Replacement. Sampling without Replacement. One-Minute Summary. Test
Yourself. Answers to Test Yourself Questions. References. 2.
Presenting Data in Charts and Tables. Presenting Categorical Data.
The Summary Table. The Bar Chart. The Pie Chart. The Pareto
Diagram. Presenting Numerical Data. The Frequency and Percentage
Distribution. Histogram. The Dot Scale Diagram. The Time-Series
Plot. The Scatter Plot. Misusing Graphs. One-Minute Summary. Test
Yourself. Answers to Test Yourself Questions. References. 3.
Descriptive Statistics for Numerical Variables. Measures of Central
Tendency. The Mean. The Median. The Mode. Quartiles. Measures of
Variation. The Range. The Variance and the Standard Deviation.
Standard (*Z*) Scores. Shape of Distributions. Symmetrical
Shape. Left-Skewed Shape. Right-Skewed Shape. The Box-and-Whisker
Plot. Important Equations. One-Minute Summary. Test Yourself.
Answers to Test Yourself Questions. References. 4. Probability.
Getting Started with Probability. Event. Elementary Event. Random
Variable. Probability. Collectively Exhaustive Events. Some Rules
of Probability. Assigning Probabilities. Classical Approach.
Empirical Approach. Subjective Approach. One-Minute Summary. Test
Yourself. Answers to Test Yourself Questions. References. 5.
Probability Distributions. Probability Distributions for Discrete
Variables. Discrete Probability Distribution. The Expected Value of
a Random Variable. Standard Deviation of a Random Variable (_). The
Binomial and Poisson Probability Distributions. The Binomial
Distribution. The Poisson Distribution. Continuous Probability
Distributions and the Normal Distribution. Normal Distribution.
Using Standard Deviation Units. Finding the *Z* Value from the
Area Under the Normal Curve. The Normal Probability Plot. Important
Equations. One-Minute Summary. Test Yourself. Answers to Test
Yourself Questions. References. 6. Sampling Distributions and
Confidence Intervals. Sampling Distributions. Sampling
Distribution. Sampling Distribution of the Mean and the Central
Limit Theorem. Sampling Distribution of the Proportion. What You
Need to Know About Sampling Distributions. Sampling Error and
Confidence Intervals. Sampling Error. Confidence Interval Estimate.
Confidence Interval Estimate for the Mean Using the **t**
Distribution (_Unknown). *t* Distribution. Confidence Interval
Estimation for the Proportion. Important Equations. One-Minute
Summary. Test Yourself. Answers to Test Yourself Questions.
References. 7. Fundamentals of Hypothesis Testing. The Null and
Alternative Hypotheses. Null Hypothesis. Alternative Hypothesis.
Hypothesis Testing Issues. Test Statistic. Practical Significance
Versus Statistical Significance. Decision-Making Risks. Type I
Error. Type II Error. Risk Trade-Off. Performing Hypothesis
Testing. The *p*-Value Approach to Hypothesis Testing.
*p*-Value. Types of Hypothesis Tests. Number of Groups.
Relationship Stated in Alternative Hypothesis *H*1. Type of
Variable. One-Minute Summary. Test Yourself. Answers to Test
Yourself Questions. References. 8. Hypothesis Testing: *Z* and
*t* Tests. Testing for the Difference between Two Proportions.
Testing for the Difference Between the Means of Two Independent
Groups. Pooled-Variance *t* Test. Pooled-Variance *t*
Test Assumptions. The Paired *t* Test. Important Equations.
One-Minute Summary. Test Yourself. Answers to Test Yourself
Questions. References. 9. Hypothesis Testing: Chi-Square Tests and
the One-Way Analysis of Variance (ANOVA). Chi-Square Test for
Two-Way Tables. One-Way Analysis of Variance (ANOVA): Testing for
the Differences among the Means of More Than Two Groups. One-Way
ANOVA. The Three Variances of ANOVA. ANOVA Summary Table. One-Way
ANOVA Assumptions. Important Equations. One-Minute Summary. Test
Yourself. Answers to Test Yourself Questions. References. 10.
Regression Analysis. Basics of Regression Analysis. Simple Linear
Regression. Determining the Simple Linear Regression Equation.
*Y* intercept. Slope. Least-Squares Method. Regression Model
Prediction. Measures of Variation. Regression Sum of Squares (SSR).
Error Sum of Squares (SSE). Total Sum of Squares (SST). The
Coefficient of Determination. The Coefficient of Correlation.
Standard Error of the Estimate. Regression Assumptions. Residual
Analysis. Residual. Evaluating the Assumptions. Inferences About
the Slope. *t* Test for the Slope. Confidence Interval
Estimate of the Slope (_1). Common Mistakes Using Regression
Analysis. Important Equations. One-Minute Summary. Test Yourself.
Answers to Test Yourself Questions. References. 11. Quality and Six
Sigma Management Applications of Statistics. Total Quality
Management. Six Sigma Management. Six Sigma. The Six Sigma DMAIC
Model. Control Charts. Special or Assignable Causes of Variation.
Chance or Common Causes of Variation. Control Limits. The *p*
Chart. The Parable of the Red Bead Experiment: Understanding
Process Variability. Deming's Red Bead Experiment. Variables
Control Charts for the Mean and Range. Important Equations.
One-Minute Summary. Test Yourself. Answers to Test Yourself
Questions. References. Appendix A: TI Statistical Calculator
Settings and Microsoft Excel Settings. TI Statistical Calculator
Settings. "Ready State" Assumptions. Menu Selections. Statistical
Function Entries by Menus. Primary Key Legend Convention. Mode
Settings. Calculator Clearing and Reset. Data Storage. Microsoft
Excel Settings. Appendix B: Review of Arithmetic and Algebra.
Assessment Quiz. Part 1. Part 2. Symbols. Addition. Subtraction.
Multiplication. Division. Fractions. Exponents and Square Roots.
Equations. Answers to Quiz. Part 1. Part 2. Appendix C: Statistical
Tables. The Cumulative Standardized Normal Distribution. Critical
Values of *t*. Critical Values of _*2*. Critical Values
of *F*. Control Chart Factors. Appendix D: Using Microsoft
Excel Wizards. Using the Chart Wizard. Choosing the Best Chart
Options. Using the PivotTable Wizard. Using the Data Analysis
Tools. Simple Linear Regression. Glossary. Index.

Now, there's an easy-to-use guide that will help you use statistics in youreveryday work or study. Experienced educators David Levine and DavidStephan help you learn statistics using plain English and with a minimum ofmathematics, but with many examples and worked-out problems.You'll benefit from reading a plain language definition for each statisticalconcept that is followed by an interpretation section that explains theimportance of the concept and how you can apply the concept to solveproblems. You'll learn about the common misconceptions about statistics thatpeople make, allowing you to better use statistics in your own work.Reinforcing your learning, you'll review lists of real-life examples orapplications of a concept or, for more advanced concepts, read completesolutions to statistical problems that include actual calculator and spreadsheetresults and illustrate how you can apply the concept to your own problems.You'll also be able to 'test yourself' at the end of a chapter to review theconcepts and methods that you leaned in the chapter.Unlike competitive books, included are 'Calculator Keys' and 'SpreadsheetSolutions' sections that provide detailed instructions for solving real problemswith a Texas Instruments statistical calculator or Microsoft Excel. For thosewith an interest in mathematics, optional 'Equation Blackboard' sections reviewthe equations that provide the foundations for important concepts.

David M. Levine isone of the world's leading innovators in
statistics education. He isProfessor Emeritus of Statistics and
Computer Information Systems at Bernard M.Baruch College (CUNY),
and co-author of several best-selling books, including
*Statisticsfor Managers using Microsoft Excel*, *Quality
Management,* and *Six Sigma for Green Belts andChampions*.
Instructional designer **DavidF. Stephan** pioneered the
classroom use of technology, and is aleader in making Excel more
accessible to statistics students. He hasco-authored several
textbooks with David M. Levine.

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