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Introductory Statistics: International Edition 9th CD 요약정보 및 구매

사용후기 0 개
지은이 Neil A. Weiss
발행년도 2015-03-01
판수 9(2014)판
페이지 912
ISBN 9781292022017
도서상태 품절
판매가격 55,000원
포인트 0점
배송비결제 주문시 결제

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  • 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.

  • Preface
    Supplements
    Technology Resources
    Data Sources

    1. The Nature of Statistics 
    1.1 Statistics Basics 
    1.2 Simple Random Sampling 
    1.3 Other Sampling Designs* 
    1.4 Experimental Designs*

    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

    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 
     
    8. Confidence Intervals for One Population Mean 
    8.1 Estimating a Population Mean 
    8.2 Confidence Intervals for One Population Mean When Is Known 
    8.3 Margin of Error 
    8.4 Confidence Intervals for One Population Mean When 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 Is Known 
    9.5 Hypothesis Tests for One Population Mean When 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

    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* 

    Appendixes
    Appendix A: Statistical Tables 
    Appendix B: Answers to Selected Exercises

    Statistical Tables
    Answers to Selected Exercises
    Index
    Photo Credits

  • Neil A. Weiss received his Ph.D. from UCLA in 1970 and subsequently accepted an assistant-professor position at Arizona State University (ASU), where he was ultimately promoted to the rank of full professor. Dr. Weiss has taught statistics, probability, and mathematics-from the freshman level to the advanced graduate level-for more than 30 years. In recognition of his excellence in teaching, he received the Dean's Quality Teaching Award from the ASU College of Liberal Arts and Sciences. Dr. Weiss' comprehensive knowledge and experience ensures that his texts are mathematically and statistically accurate, as well as pedagogically sound.
    In addition to his numerous research publications, Dr. Weiss is the author of A Course in Probability (Addison-Wesley, 2006). He has also authored or coauthored books in finite mathematics, statistics, and real analysis, and is currently working on a new book on applied regression analysis and the analysis of variance. His texts-well known for their precision, readability, and pedagogical excellence-are used worldwide. 
    Dr. Weiss is a pioneer of the integration of statistical software into textbooks and the classroom, first providing such integration over 20 years ago in the book Introductory Statistics (Addison-Wesley, 1982). Weiss and Addison-Wesley continue that pioneering spirit to this day with the inclusion of some of the most comprehensive Web sites in the field.
    In his spare time, Dr. Weiss enjoys walking, studying and practicing meditation, and playing hold 'em poker. He is married and has two sons.

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