Elementary Statistics: United States Edition
Autor Neil A. Weissen Limba Engleză Mixed media product – 7 mai 2007
This new edition continues the author’s tradition of cutting-edge statistical pedagogy and seamless integration of technology, and includes hundreds of new exercises with carefully cited data from journals, magazines, newspapers, and Web sites.
Elementary Statistics, Seventh Edition, is the ideal text for instructors who teach a one-semester course and prefer a briefer presentation of topics.
Datasets and other resources (where applicable) for this book are available here.
Preț: 697.49 lei
Preț vechi: 905.84 lei
-23% Nou
Puncte Express: 1046
Preț estimativ în valută:
133.48€ • 139.18$ • 110.93£
133.48€ • 139.18$ • 110.93£
Carte indisponibilă temporar
Doresc să fiu notificat când acest titlu va fi disponibil:
Se trimite...
Preluare comenzi: 021 569.72.76
Specificații
ISBN-13: 9780321422095
ISBN-10: 0321422090
Pagini: 744
Dimensiuni: 216 x 254 x 19 mm
Greutate: 1.71 kg
Ediția:Nouă
Editura: Pearson Education
Colecția Pearson Education
Locul publicării:Upper Saddle River, United States
ISBN-10: 0321422090
Pagini: 744
Dimensiuni: 216 x 254 x 19 mm
Greutate: 1.71 kg
Ediția:Nouă
Editura: Pearson Education
Colecția Pearson Education
Locul publicării:Upper Saddle River, United States
Cuprins
Preface
Supplements List
Data Sources
PART I INTRODUCTION
Chapter 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
Chapter 2 Organizing Data
2.1 Variables and Data
2.2 Grouping Data
2.3 Graphs and Charts
2.4 Distribution Shapes
2.5 Misleading Graphs
Chapter 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
Chapter 4 Descriptive Methods in Regression and Correlation
4.1 Linear Equations With One Independent Variable
4.2 The Regression Equation
4.3 The Coefficient of Determination
4.4 Linear Correlation
PART III PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS
Chapter 5 Probability and Random Variables
5.1 Probability Basics
5.2 Events
5.3 Some Rules of Probability
5.4 Discrete Random Variables and Probability Distributions*
5.5 The Mean and Standard Deviation of a Discrete Random Variable*
5.6 The Binomial Distribution*
Chapter 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
Chapter 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
Chapter 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
Chapter 9 Hypothesis Tests for One Population Mean
9.1 The Nature of Hypothesis Testing
9.2 Terms, Errors, and Hypotheses
9.3 Hypothesis Tests for One Population Mean When ? is Known
9.4 P-Values
9.5 Hypothesis Tests for One Population Mean When ? is Unknown
Chapter 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 Inferences for Two Population Means, Using Paired Samples
Chapter 11 Inferences for Population Proportions
11.1 Confidence Intervals for One Population Proportion
11.2 Hypothesis Tests for One Population Proportion
11.3 Inferences for Two Population Proportions
Chapter 12 Chi-Square Procedures
12.1 The Chi-Square Distribution
12.2 Chi-Square Goodness-of-Fit Test
12.3 Contingency Tables; Association
12.4 Chi-Square Independence Test
Chapter 13 Analysis of Variance (ANOVA)
13.1 The F-Distribution
13.2 One-Way ANOVA: The Logic
13.3 One-Way ANOVA: The Procedure
Chapter 14 Inferential Methods in Regression and Correlation
14.1 The Regression Model; Analysis of Residuals
14.2 Inferences for the Slope of the Population Regression Line
14.3 Estimation and Prediction
14.4 Inferences in Correlation
APPENDIXES
Appendix A Statistical Tables
I Random numbers
II Areas under the standard normal curve
III Normal scores
IV Values of tα
V Values of χα2
VI Values of Fα
VII Binomial probabilities
Appendix B Answers to Selected Exercises
*indicates an optinoal section
Supplements List
Data Sources
PART I INTRODUCTION
Chapter 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
Chapter 2 Organizing Data
2.1 Variables and Data
2.2 Grouping Data
2.3 Graphs and Charts
2.4 Distribution Shapes
2.5 Misleading Graphs
Chapter 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
Chapter 4 Descriptive Methods in Regression and Correlation
4.1 Linear Equations With One Independent Variable
4.2 The Regression Equation
4.3 The Coefficient of Determination
4.4 Linear Correlation
PART III PROBABILITY, RANDOM VARIABLES, AND SAMPLING DISTRIBUTIONS
Chapter 5 Probability and Random Variables
5.1 Probability Basics
5.2 Events
5.3 Some Rules of Probability
5.4 Discrete Random Variables and Probability Distributions*
5.5 The Mean and Standard Deviation of a Discrete Random Variable*
5.6 The Binomial Distribution*
Chapter 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
Chapter 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
Chapter 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
Chapter 9 Hypothesis Tests for One Population Mean
9.1 The Nature of Hypothesis Testing
9.2 Terms, Errors, and Hypotheses
9.3 Hypothesis Tests for One Population Mean When ? is Known
9.4 P-Values
9.5 Hypothesis Tests for One Population Mean When ? is Unknown
Chapter 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 Inferences for Two Population Means, Using Paired Samples
Chapter 11 Inferences for Population Proportions
11.1 Confidence Intervals for One Population Proportion
11.2 Hypothesis Tests for One Population Proportion
11.3 Inferences for Two Population Proportions
Chapter 12 Chi-Square Procedures
12.1 The Chi-Square Distribution
12.2 Chi-Square Goodness-of-Fit Test
12.3 Contingency Tables; Association
12.4 Chi-Square Independence Test
Chapter 13 Analysis of Variance (ANOVA)
13.1 The F-Distribution
13.2 One-Way ANOVA: The Logic
13.3 One-Way ANOVA: The Procedure
Chapter 14 Inferential Methods in Regression and Correlation
14.1 The Regression Model; Analysis of Residuals
14.2 Inferences for the Slope of the Population Regression Line
14.3 Estimation and Prediction
14.4 Inferences in Correlation
APPENDIXES
Appendix A Statistical Tables
I Random numbers
II Areas under the standard normal curve
III Normal scores
IV Values of tα
V Values of χα2
VI Values of Fα
VII Binomial probabilities
Appendix B Answers to Selected Exercises
*indicates an optinoal section
Notă biografică
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.
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.
Caracteristici
- Real- World Examples: Every concept discussed in the text is illustrated by at least one detailed, compelling and illustrative example based on real-life situations.
- Real Data Sources: Neil Weiss includes carefully cited data from reputable journals, newspapers, magazines and Web sites to help students see the integration of statistics in everyday life.
- Interpretation Boxes explain the meaning and significance of statistical results in every day life and highlight the importance of interpreting answers and results.
- What Does It Mean? boxes state, in "plain English," the meaning of definitions, formulas, and key facts. This feature also summarizes relevant discussions.
- Procedure Boxes have been enhanced to include the "why, when, and how" of the methods. Each procedure box has a brief identifying title followed by a statement of its purpose (why it's used), the assumptions for its use (when it's used), and the steps for applying the procedure (how it's used).
- Parallel Critical-Value/P-Value Approaches: Through a parallel presentation, this text offers complete flexibility in the coverage of critical-value and P-value approaches to hypothesis testing. Instructors can focus on one approach, or they can cover and compare both approaches.
- Parallel Presentations of Technology offer complete flexibility in the coverage of technology which includes options for the use of MINITAB®, Excel®, and the TI-83 and TI-84 Plus graphing calculators. One or more technologies can be explored and compared. Instructions and output for each package are included in Technology Centers throughout the book.
- Technology Appendixes for Minitab, Excel and the TI-83/84 Plus graphing calculator introduce these statistical technologies, explain how to input data, and discuss how to perform basic tasks. These appendixes are located in the Technology Basics folder of the WeissStats CD (bound in the back of the text
Caracteristici noi
- Streamlined Presentation: The new editions have been rewritten to reveal the superior, clear instruction for which Weiss is well known. This streamlined presentation seamlessly blends solid statistics (and the mathematics behind it) with a clear and effective teaching style. Students find these books readable and clear, and instructors appreciate that the math level is right for a diverse population.
- Hundreds of new and updated Exercises have been added to each section and reorganized into the following categories:
- Understanding Concepts and Skills
- Working with Large Data Sets
- Extending the Concepts and Skills
- New You Try It! feature, which follows most worked examples, allows students to immediately check their understanding by directing them to a similar exercise for them to solve on their own.
- Expanded Focusing on Data Analysis sections at the end of each chapter now include a Focus Sample file that contains data on the same 13 variables for a simple random sample of 200 undergraduate students at the University of Wisconsin — Eau Claire. These 200 students constitute a sample that can be used for making numerous statistical references.
- New Case Studies: More than one-third of the chapter opener case studies are new.
- New Technology Appendixes by the author help students use Minitab, Excel, and the TI 83/84 Plus graphing calculators. These appendixes, located on the CD-ROM packaged with new copies of the book, introduce the technology and methods for using it to work with data.
- The WeissStats CD-ROM included in every new copy of the textbook includes data sets in multiple formats; Data Desk/XL (DDXL) software, an Excel add-in; and optional text chapters that cover multiple regression analysis, model building in regression, and design of experiments and two-way analysis of variance.
- MyStatLab provides instructors with a rich and flexible set of course materials, along with course-management tools that make it easy to deliver all or a portion of your course online. MyStatLab provides students with a personalized interactive learning environment, where they can learn at their own pace and measure their progress. www.mystatlab.com
- StatCrunch is a powerful online tool that provides an interactive environment for doing statistics. Students can use StatCrunch for both numerical and graphical data analysis, taking advantage of interactive graphics to help them see the connection between objects selected in a graph and the underlying data. StatCrunch is available within the MyStatLab course.