First Course in Statistics, A, Global Edition

Series
Pearson
Author
James T. McClave / Terry T Sincich  
Publisher
Pearson
Cover
Softcover
Edition
12
Language
English
Total pages
640
Pub.-date
January 2018
ISBN13
9781292165417
ISBN
1292165413
Related Titles


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First Course in Statistics, A, Global Edition
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Description

For courses in introductory statistics.

This package includes Pearson MyLab Statistics.

 

A Contemporary Classic

Classic, yet contemporary; theoretical, yet applied--McClave & Sincich’s A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises.

 

Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra. Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.

 

This package includes Pearson MyLab Statistics, an online homework, tutorial, and assessment program designed to work with this text to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

 

Pearson MyLab Statistics should only be purchased when required by an instructor. Please be sure you have the correct ISBN and Course ID. Instructors, contact your Pearson representative for more information.

Features

This title is a Pearson Global Edition. The Editorial team at Pearson has worked closely with educators around the world to include content, which is especially relevant to students outside the United States.

·    McClave and Sincich provide support to students when they are learning to solve problems and when they are studying and reviewing the material.

o “Where We’re Going” bullets begin each chapter, offering learning objectives and providing section numbers that correspond to where each concept is discussed in the chapter.

o Examples foster problem-solving skills by taking a three-step approach: (1) "Problem", (2) "Solution", and (3) "Look Back" (or "Look Ahead"). This step-by-step process provides students with a defined structure by which to approach problems and enhances their problem-solving skills.

o The "Look Back" feature gives helpful hints for solving the problem and/or provides a further reflection or insight into the concept or procedure that is covered.

o A “Now Work” exercise suggestion follows each Example, which provides a practice exercise that is similar in style and concept to the example. Students test and confirm their understanding immediately.

o End-of-chapter summaries now serve as a more effective study aid for students. Important points are reinforced through flow graphs (which aid in selecting the appropriate statistical method) and boxed notes with key words, formulas, definitions, lists, and key concepts.

·    More than 1,000 exercises are included, based on a wide variety of applications in various disciplines and research areas, and more than 35% have been updated for the new edition. Some students have difficulty learning the mechanics of statistical techniques while applying the techniques to real applications. For this reason, exercise sections are divided into four parts:

o Learning the Mechanics: These exercises allow students to test their ability to comprehend a mathematical concept or a definition.

o Applying the ConceptsBasic: Based on applications taken from a wide variety of journals, newspapers, and other sources, these short exercises help students begin developing the skills necessary to diagnose and analyze real-world problems.

o Applying the Concepts—Intermediate: Based on more detailed real-world applications, these exercises require students to apply their knowledge of the technique presented in the section.

o Applying the Concepts—Advanced: These more difficult real-data exercises require students to use critical thinking skills.

o Critical Thinking Challenges: Students apply critical thinking skills to solve one or two challenging real-life problems. These expose students to real-world problems with solutions that are derived from careful, logical thought and use of the appropriate statistical analysis tool.

·    Case studies, applications, and biographies keep students motivated and show the relevance of statistics.

o Ethics Boxes have been added where appropriate to highlight the importance of ethical behavior when collecting, analyzing, and interpreting statistical data.

o Statistics in Action begins each chapter with a case study based on an actual contemporary, controversial, or high-profile issue. Relevant research questions and data from the study are presented and the proper analysis demonstrated in short "Statistics in Action Revisited" sections throughout the chapter.

o Brief Biographies of famous statisticians and their achievements are presented within the main chapter, as well as in marginal boxes. Students develop an appreciation for the statistician's efforts and the discipline of statistics as a whole.

·    Support for statistical software is integrated throughout the text and online, so instructors can focus less time on teaching the software and more time teaching statistics.

o Each statistical analysis method presented is demonstrated using output from SAS, SPSS, and MINITAB. These outputs appear in examples and exercises, exposing students to the output they will encounter in their future careers.

o Using Technology boxes at the end of each chapter offer statistical software tutorials, with step-by-step instructions and screenshots for MINITAB and, where appropriate, the TI-83/84 Plus Graphing Calculator.

o To complement the text, support for the statistical software is available in Pearson MyLab Statistics’ Technology Instruction. Student discounts on select statistical software packages are also available. Ask your Pearson representative for details.

·    Flexibility in Coverage

o Probability and Counting Rules:

§  Probability poses a challenge for instructors because they must decide on the level of presentation, and students find it a difficult subject to comprehend.

§  Unlike other texts that combine probability and counting rules, McClave/Sincich includes the counting rules (with examples) in an appendix rather than in the body of the chapter on probability; the instructor can control the level of coverage of probability covered.

o Multiple Regression and Model Building:

§  Two full chapters are devoted to discussing the major types of inferences that can be derived from a regression analysis, showing how these results appear in the output from statistical software, and, most important, selecting multiple regression models to be used in an analysis.

§  The instructor has the choice of a one-chapter coverage of simple linear regression (Chapter 11), a two-chapter treatment of simple and multiple regression (excluding the sections on model building in Chapter 12), or complete coverage of regression analysis, including model building and regression diagnostics.

§  This extensive coverage of such useful statistical tools will provide added evidence to the student of the relevance of statistics to real-world problems.

o Additional online resources include files for text examples, exercises, Statistics in Action and Real-World case data sets marked with a data set icon. Also available is Chapter 14, Nonparametric Statistics, and a set of applets that allow students to run simulations that visually demonstrate some of the difficult statistical concepts (e.g., sampling distributions and confidence intervals).

o Role of calculus:

§  Although the text is designed for students without a calculus background, footnotes explain the role of calculus in various derivations.

§  Footnotes are also used to inform the student about some of the theory underlying certain methods of analysis. They provide additional flexibility in the mathematical and theoretical level at which the material is presented.

This package includes Pearson MyLab Statistics, an online homework, tutorial, and assessment program designed to work with this text to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

· NEW! 30% new and updated exercises give students more of the practice they need to succeed.

· NEW! StatCrunch applets have been updated to run in HTML5, so that they are more accessible and will run on most computers and tablets without additional plugins.

· NEW! Data-informed updates: the authors have analyzed aggregated student usage and performance data from the previous edition's Pearson MyLab Statistics course. The results of this analysis helped improved the quality and quantity of exercises that matter most to instructors and students.

New to this Edition

·    30% of the 1,000+ exercises are updated or new, based on contemporary studies and real data. Most of these exercises foster and promote critical thinking skills.

·    Updated technology: all printouts from statistical software (SAS, SPSS, MINITAB, and the TI-83/Tl-84 Plus Graphing Calculator) and corresponding instructions for use have been revised to reflect the latest versions of the software.

·    New Statistics in Action Cases: six of the 14 cases are new or updated, each based on real data from a recent study.

·    Continued emphasis on Ethics: where appropriate, boxes have been added emphasizing the importance of ethical behavior when collecting, analyzing, and interpreting data with statistics.

Content Changes

·    Chapter 1 (Statistics, Data, and Statistical Thinking): Material on all basic sampling concepts (e.g., random sampling and sample survey designs) has been streamlined and moved to Section 1.5 (Collecting Data: Sampling and Related Issues).

·    Chapter 2 (Methods for Describing Sets of Data): The section on summation notation has been moved to the appendix (Appendix A). Also, recent examples of misleading graphics have been added to Section 2.10 (Distorting the Truth with Descriptive Statistics).

·    Chapter 4 (Random Variables and Probability Distributions): Use of technology for computing probabilities of random variables with known probability distributions (e.g., binomial and normal distributions) has been incorporated into the relevant sections of this chapter. This reduces the use of tables of probabilities for these distributions.

·    Chapter 6 (Tests of Hypothesis): The section on p-values in hypothesis testing (Section 6.3) has been moved up to emphasize the importance of their use in real-life studies. Throughout the remainder of the text, conclusions from a test of hypothesis are based on p-values.

This package includes Pearson MyLab Statistics, an online homework, tutorial, and assessment program designed to work with this text to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.

·    30% new and updated exercises give students more of the practice they need to succeed.

·    StatCrunch applets have been updated to run in HTML5, so that they are more accessible and will run on most computers and tablets without additional plugins.

·    Data-informed updates: the authors have analyzed aggregated student usage and performance data from the previous edition's Pearson MyLab Statistics course. The results of this analysis helped improved the quality and quantity of exercises that matter most to instructors and students.

 

Table of Contents

1. Statistics, Data, and Statistical Thinking

1.1 The Science of Statistics

1.2 Types of Statistical Applications

1.3 Fundamental Elements of Statistics

1.4 Types of Data

1.5 Collecting Data: Sampling and Related Issues

1.6 The Role of Statistics in Critical Thinking and Ethics

Statistics in Action: Social Media Network Usage—Are You Linked In?

Using Technology: MINITAB: Accessing and Listing Data

2. Methods for Describing Sets of Data

2.1 Describing Qualitative Data

2.2 Graphical Methods for Describing Quantitative Data

2.3 Numerical Measures of Central Tendency

2.4 Numerical Measures of Variability

2.5 Using the Mean and Standard Deviation to Describe Data

2.6 Numerical Measures of Relative Standing

2.7 Methods for Detecting Outliers: Box Plots and z-Scores

2.8 Graphing Bivariate Relationships (Optional)

2.9 Distorting the Truth with Descriptive Statistics

Statistics in Action: Body Image Dissatisfaction: Real or Imagined?

Using Technology: MINITAB: Describing Data

TI-83/TI–84 Plus Graphing Calculator: Describing Data

3. Probability

3.1 Events, Sample Spaces, and Probability

3.2 Unions and Intersections

3.3 Complementary Events

3.4 The Additive Rule and Mutually Exclusive Events

3.5 Conditional Probability

3.6 The Multiplicative Rule and Independent Events

Statistics in Action: Lotto Buster! Can You Improve Your Chance of Winning?

Using Technology: TI-83/TI-84 Plus Graphing Calculator: Combinations and Permutations

4. Random Variables and Probability Distributions

4.1 Two Types of Random Variables

4.2 Probability Distributions for Discrete Random Variables

4.3 The Binomial Random Variable

4.4 Probability Distributions for Continuous Random Variables

4.5 The Normal Distribution

4.6 Descriptive Methods for Assessing Normality

4.7 Approximating a Binomial Distribution with a Normal Distribution (Optional)

4.8 Sampling Distributions

4.9 The Sampling Distribution of and the Central Limit Theorem

Statistics in Action: Super Weapons Development – Is the Hit Ratio Optimized?

Using Technology: MINITAB: Discrete Probabilities

 

5. Inferences Based on a Single Sample

5.1 Identifying and Estimating the Target Parameter

5.2 Confidence Interval for a Population Mean: Normal (z) Statistic

5.3 Confidence Interval for a Population Mean: Student’s t-Statistic

5.4 Large-Sample Confidence Interval for a Population Proportion

5.5 Determining the Sample Size

5.6 Confidence Interval for a Population Variance (Optional)

Statistics in Action: Medicare Fraud Investigations

Using Technology: MINITAB: Confidence Intervals

6. Inferences Based on a Single Sample

6.1 The Elements of a Test of Hypothesis

6.2 Formulating Hypotheses and Setting Up the Rejection Region

6.3 Observed Significance Levels: p-values

6.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic

6.5 Test of Hypothesis about a Population Mean: Student’s t-Statistic

6.6 Large-Sample Test of Hypothesis about a Population Proportion

6.7 Test of Hypothesis about a Population Variance (Optional)

6.8 A Nonparametric Test about a Population Median (Optional)

Statistics in Action: Diary of a KLEENEX User How Many Tissues in a Box?

Using Technology: MINITAB: Tests of Hypotheses

TI-83/TI-84 Plus Graphing Calculator: Tests of Hypotheses

7. Comparing Population Means

7.1 Identifying the Target Parameter

7.2 Comparing Two Population Means: Independent Sampling

7.3 Comparing Two Population Means: Paired Difference Experiments

7.4 Determining the Sample Size

7.5 A Nonparametric Test for Comparing Two Populations: Independent Samples

7.6 A Nonparametric Test for Comparing Two Populations: Paired Difference Experiment (Optional)

7.7 Comparing Three or More Population Means: Analysis of Variance (Optional)

Statistics in Action: Zixlt Corp. vs. Visa USA Inc. – A Libel Case

Using Technology: MINITAB: Comparing Means

TI-83/TI-84 Plus Graphing Calculator: Comparing Means

 

8. Comparing Population Proportions

8.1 Comparing Two Population Proportions: Independent Sampling

8.2 Determining Sample Size

8.3 Testing Category Probabilities: Multinomial Experiment

8.4 Testing Categorical Probabilities: Two-Way (Contingency) Table

9. Simple Linear Regression

9.1 Probabilistic Models

9.2 Fitting the Model: The Least Squares Approach

9.3 Model Assumptions

9.4 Assessing the Utility of the Model: Making Inferences about the Slope β1

9.5 The Coefficients of Correlation and Determination

9.6 Using the Model for Estimation and Prediction

9.7 A Complete Example

9.8 A Nonparametric Test for Correlation (Optional)

Statistics in Action: Can “Dowsers” Really Detect Water?

 Using Technology: MINITAB: Simple Linear Regression

TI-83/TI-84 Plus Graphing Calculator: Simple Linear Regression

Appendices

Short Answers to Selected Odd-Numbered Exercises

Index

Photo Credits