Introductory Statistics Plus MyStatLab with Pearson eText -- Access Card Package

ALERT: Before you purchase, check with your instructor or review your course syllabus to ensure that you select the correct ISBN. Several versions of Pearson's MyLab & Mastering products exist for each title, including customized versions for individual schools, and registrations are not transferable. In addition, you may need a CourseID, provided by your instructor, to register for and use Pearson's MyLab & Mastering products.   Packages Access codes for Pearson's MyLab & Mastering products may not be included when purchasing or renting from companies other than Pearson; check with the seller before completing your purchase.   Used or rental books If you rent or purchase a used book with an access code, the access code may have been redeemed previously and you may have to purchase a new access code.   Access codes Access codes that are purchased from sellers other than Pearson carry a higher risk of being either the wrong ISBN or a previously redeemed code. Check with the seller prior to purchase.   -- Weiss’s Introductory Statistics, Ninth Edition is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. The text is suitable for a one- or two-semester course. Comprehensive in its coverage, Weiss’s meticulous style offers careful, detailed explanations to ease the learning process. With more than 1,000 data sets and more than 2,600 exercises, most using real data, this text takes a data-driven approach that encourages students to apply their knowledge and develop statistical literacy.   Introductory Statistics, Ninth Edition, contains parallel presentation of critical-value and p-value approaches to hypothesis testing. This unique design allows both the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two.   This edition continues the book’s tradition of being on the cutting edge of statistical pedagogy, technology, and data analysis. It includes hundreds of new and updated exercises with real data from journals, magazines, newspapers, and websites.   Datasets and other resources (where applicable) for this book are available here.

Table of Contents:
Preface Course Management Notes (Instructor’s Edition only) Supplements Technology Resources Data Sources   Part I: Introduction   1. The Nature of Statistics 1.1 Statistics Basics 1.2 Simple Random Sampling 1.3 Other Sampling Designs* 1.4 Experimental Designs*   Part II: Descriptive Statistics   2. Organizing Data 2.1 Variables and Data 2.2 Organizing Qualitative Data 2.3 Organizing Quantitative Data 2.4 Distribution Shapes 2.5 Misleading Graphs*   3. Descriptive Measures 3.1 Measures of Center 3.2 Measures of Variation 3.3 The Five-Number Summary; Boxplots 3.4 Descriptive Measures for Populations; Use of Samples   Part III: Probability, Random Variables, and Sampling Distributions   4. Probability Concepts 4.1 Probability Basics 4.2 Events 4.3 Some Rules of Probability 4.4 Contingency Tables; Joint and Marginal Probabilities* 4.5 Conditional Probability* 4.6 The Multiplication Rule; Independence* 4.7 Bayes’s Rule* 4.8 Counting Rules*   5. Discrete Random Variables* 5.1 Discrete Random Variables and Probability Distributions* 5.2 The Mean and Standard Deviation of a Discrete Random Variable* 5.3 The Binomial Distribution* 5.4 The Poisson Distribution*   6. The Normal Distribution 6.1 Introducing Normally Distributed Variables 6.2 Areas Under the Standard Normal Curve 6.3 Working with Normally Distributed Variables 6.4 Assessing Normality; Normal Probability Plots 6.5 Normal Approximation to the Binomial Distribution*   7. The Sampling Distribution of the Sample Mean 7.1 Sampling Error; the Need for Sampling Distributions 7.2 The Mean and Standard Deviation of the Sample Mean 7.3 The Sampling Distribution of the Sample Mean   Part IV: Inferential Statistics   8. Confidence Intervals for One Population Mean 8.1 Estimating a Population Mean 8.2 Confidence Intervals for One Population Mean When σ Is Known 8.3 Margin of Error 8.4 Confidence Intervals for One Population Mean When σ Is Unknown   9. Hypothesis Tests for One Population Mean 9.1 The Nature of Hypothesis Testing 9.2 Critical-Value Approach to Hypothesis Testing 9.3 P-Value Approach to Hypothesis Testing 9.4 Hypothesis Tests for One Population Mean When σ Is Known 9.5 Hypothesis Tests for One Population Mean When σ Is Unknown 9.6 The Wilcoxon Signed-Rank Test* 9.7 Type II Error Probabilities; Power* 9.8 Which Procedure Should Be Used?*   10. Inferences for Two Population Means 10.1 The Sampling Distribution of the Difference between Two Sample Means for Independent Samples 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal 10.4 The Mann–Whitney Test* 10.5 Inferences for Two Population Means, Using Paired Samples 10.6 The Paired Wilcoxon Signed-Rank Test* 10.7 Which Procedure Should Be Used?*   11. Inferences for Population Standard Deviations* 11.1 Inferences for One Population Standard Deviation* 11.2 Inferences for Two Population Standard Deviations, Using Independent Samples*   12. Inferences for Population Proportions 12.1 Confidence Intervals for One Population Proportion 12.2 Hypothesis Tests for One Population Proportion 12.3 Inferences for Two Population Proportions   13. Chi-Square Procedures 13.1 The Chi-Square Distribution 13.2 Chi-Square Goodness-of-Fit Test 13.3 Contingency Tables; Association 13.4 Chi-Square Independence Test 13.5 Chi-Square Homogeneity Test   Part V: Regression, Correlation, and ANOVA   14. Descriptive Methods in Regression and Correlation 14.1 Linear Equations with One Independent Variable 14.2 The Regression Equation 14.3 The Coefficient of Determination 14.4 Linear Correlation   15. Inferential Methods in Regression and Correlation 15.1 The Regression Model; Analysis of Residuals 15.2 Inferences for the Slope of the Population Regression Line 15.3 Estimation and Prediction 15.4 Inferences in Correlation 15.5 Testing for Normality*   16. Analysis of Variance (ANOVA) 16.1 The F-Distribution 16.2 One-Way ANOVA: The Logic 16.3 One-Way ANOVA: The Procedure 16.4 Multiple Comparisons* 16.5 The Kruskal–Wallis Test*   Part VI: Multiple Regression and Model Building; Experimental Design and ANOVA (On The WeissStats CD-ROM)   Module A. Multiple Regression Analysis A.1 The Multiple Linear Regression Model A.2 Estimation of the Regression Parameters A.3 Inferences Concerning the Utility of the Regression Model A.4 Inferences Concerning the Utility of Particular Predictor Variables A.5 Confidence Intervals for Mean Response; Prediction Intervals for Response A.6 Checking Model Assumptions and Residual Analysis   Module B. Model Building in Regression B.1 Transformations to Remedy Model Violations B.2 Polynomial Regression Model B.3 Qualitative Predictor Variables B.4 Multicollinearity B.5 Model Selection: Stepwise Regression B.6 Model Selection: All Subsets Regression B.7 Pitfalls and Warnings   Module C. Design of Experiments and Analysis of Variance C.1 Factorial Designs C.2 Two-Way ANOVA: The Logic C.3 Two-Way ANOVA: The Procedure C.4 Two-Way ANOVA: Multiple Comparisons C.5 Randomized Block Designs C.6 Randomized Block ANOVA: The Logic C.7 Randomized Block ANOVA: The Procedure C.8 Randomized Block ANOVA: Multiple Comparisons C.9 Friedman’s Nonparametric Test for the Randomized Block Design*   APPENDICES Appendix A: Statistical Tables I. Random numbers II. Areas under the standard normal curve III. Normal scores IV. Values of tα V. Values of Wα VI. Values of Mα VII. Values of χα2 VIII. Values of Fα IX. Critical values for a correlation test for normality X. Values of q0.01 XI. Values of q0.05 XII. Binomial probabilities   Appendix B Answers to Selected Exercises Index Photo Credits Indexes for Biographical Sketches & Case Studies   WeissStats CD-ROM (included with every new textbook) Brief Contents Note: See the WeissStats CD ReadMe file for detailed contents. Applets Data Sets DDXL (Excel Add-In) Detailed t and Chi-square Tables Focus Database Formulas and Appendix A Tables JMP Concept Discovery Modules Minitab Macros Regression-ANOVA Modules Technology Basics TI Programs   *indicates an optional section