IES Management College And Research Centre

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Statistics for business and economics

By: Analytics: Show analyticsPublication details: Andover Cengage Learning India Private Limited 2019Edition: 12Description: xxxii,1088 PaperbackISBN:
  • 978-81-315-2813-8
Subject(s): DDC classification:
  • 519.5/And/Swe/Wil
Contents:
Preface. 1. Data and Statistics. 2. Descriptive Statistics: Tabular and Graphical Displays. 3. Descriptive Statistics: Numerical Measures. 4. Introduction to Probability. 5. Discrete Probability Distributions. 6. Continuous Probability Distributions. 7. Sampling and Sampling Distributions. 8. Interval Estimation. 9. Hypothesis Tests. 10. Inference about Means and Proportions with Two Populations. 11. Inferences about Population Variances. 12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit. 13. Experimental Design and Analysis of Variance. 14. Simple Linear Regression. 15. Multiple Regression. 16. Regression Analysis: Model Building. 17. Time Series Analysis and Forecasting. 18. Nonparametric Methods. 19. Statistical Methods for Quality Control. 20. Index Numbers. Appendix A. References and Bibliography. Appendix B. Tables. Appendix C. Summation Notation. Appendix D. Self-Test Solutions and Answers to Even –Numbered Exercises. Appendix E. Microsoft Excel 2010 and Tools for Statistical Analysis. Appendix F. Computing p-Values Using Minitab and Excel. Index.
Summary: The authors bring more than twenty-five years of unmatched experience to this text, along with sound statistical methodology, a proven problem-scenario approach, and meaningful applications that clearly demonstrate how statistical information informs decisions in the business world. Thoroughly updated, the text's more than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. And, to give you the most relevant text you can get for your course, you the topics you want, including coverage of popular commercial statistical software programs like Minitab 16 and Excel 2010, along with StatTools and other leading Excel 2010 statistical add-ins. TRUSTED TEAM OF EXPERT AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. As prominent, respected leaders and active consultants in business and statistics today, authors David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, now joined by Jeffrey D. Camm and James J. Cochran provide an accurate presentation of statistical concepts you can trust with every edition. LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENT UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text, this unique approach helps students understand statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how statistics are used within business today to solve problems. SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and learn the use of techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems. USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare today’s students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today’s statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing. SIMPLIFIED INTRODUCTION TO P-VALUES CLARIFIES UNDERSTANDING FOR STUDENTS. As in the previous edition, this edition emphasizes the use of p-values as the preferred approach to hypothesis testing. To further clarify the introduction of this concept for students, the authors now separate a simplified conceptual definition of p-values from operational definitions that clarify how the p-value is computed for a lower-tail test, an upper-tail test, and a two-tail test. STUDENTS LEARN TO USE SOFTWARE TO COMPUTE P-VALUES. For your flexibility, an optional appendix clearly demonstrates how to use MINITAB and Excel to compute p-values associated with z, t, and F test statistics. This coverage is particularly helpful when discussing hypothesis testing (Chs. 9-16). Descriptive Statistics--Chapters 2 and 3. We have significantly revised these chapters to incorporate new material on data visualization, best practices, and much more. Chapter 2 has been reorganized to include new material on side-by-side and stacked bar charts, and a new section has been added on data visualization and best practices I creating effective displays. Chapter 3 now includes coverage of the geometric mean in the section on measures of location. The geometric mean has many applications in the computation of growth rates for financial assets, annual percentage rates, and so on. Chapter 3 also includes a new section on data dashboards and how summary statistics can be incorporated to enhance their effectiveness. Discrete Probability Distributions--Chapter 5. The introductory material in this chapter has been revised to better explain the role of probability distributions and to show how the material on assigning probabilities in Chapter 4 can be used to develop discrete probability distributions. We point out that the empirical discrete probability distribution is developed by using the relative frequency method to assign probabilities. At the request of many users, we have added a new Section 5.4 that covers bivariate discrete distributions and financial applications. We show how financial portfolios can be constructed and analyzed using these distributions. Chapter 12--Comparing Multiple Proportions, Tests of Independence, and Goodness of Fit. This chapter has undergone a major revision. We have added a new section on testing the equality of three or more population proportions. This section includes a procedure for making multiple comparison tests between all pairs of population proportions. The section on the test of independence has been rewritten to clarify that the test concerns the independence of two categorical variables. Revised appendixes with step-by-step instructions for Minitab, Excel, and StatTools are included. New Case Problems. We have added 8 new case problems to this edition; the total number of cases is 31. Three new descriptive statistics cases have been added to chapters 2 and 3. Five new case problems involving regression appear in Chapters 14, 15, and 16. These case problems provide students with the opportunity to analyze larger data sets and prepare managerial reports based on the results of their analysis. New Statistics in Practice Applications. Each chapter begins with a Statistics in Practice vignette that describes an application of the statistical methodology to be covered in the chapter. New to this edition is a Statistics in Practice for Chapter 2 describing the use of data dashboards and data visualization at the Cincinnati Zoo and Botanical Garden. We have also added a Statistics i Practice to Chapter 4 describing how a NASA team used probability to assist in the rescue of 33 Chilean miners trapped by a cave-in. New Examples and Exercises based on Real Data. We continue to make a significant effort to update our text examples and exercises with the most current real data and referenced sources of statistical information. In this edition, we have added approximately 180 new examples and exercises based on real data and referenced sources. Using data from sources also used by The Wall Street Journal, USA Today, Barron's, and others, we have drawn from actual studies to develop explanations and to create exercises that demonstrate the many uses of statistics in business and economics. We believe that the use of real data helps generate more student interest in the material and enables the student to learn about both the statistical methodology and its application. The twelfth edition contains over 350 examples and exercises based on real data.
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Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136732
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136733
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136734
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136735
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136736
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136737
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136738
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136739
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136740
Student Collection Student Collection Main Library 519.5/ And/Swe/Student Collection (Browse shelf(Opens below)) Available 11136741
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Preface.

1. Data and Statistics.

2. Descriptive Statistics: Tabular and Graphical Displays.

3. Descriptive Statistics: Numerical Measures.

4. Introduction to Probability.

5. Discrete Probability Distributions.

6. Continuous Probability Distributions.

7. Sampling and Sampling Distributions.

8. Interval Estimation.

9. Hypothesis Tests.

10. Inference about Means and Proportions with Two Populations.

11. Inferences about Population Variances.

12. Comparing Multiple Proportions, Test of Independence and Goodness of Fit.

13. Experimental Design and Analysis of Variance.

14. Simple Linear Regression.

15. Multiple Regression.

16. Regression Analysis: Model Building.

17. Time Series Analysis and Forecasting.

18. Nonparametric Methods.

19. Statistical Methods for Quality Control.

20. Index Numbers.

Appendix A. References and Bibliography.

Appendix B. Tables.

Appendix C. Summation Notation.

Appendix D. Self-Test Solutions and Answers to Even –Numbered Exercises.

Appendix E. Microsoft Excel 2010 and Tools for Statistical Analysis.

Appendix F. Computing p-Values Using Minitab and Excel.

Index.

The authors bring more than twenty-five years of unmatched experience to this text, along with sound statistical methodology, a proven problem-scenario approach, and meaningful applications that clearly demonstrate how statistical information informs decisions in the business world. Thoroughly updated, the text's more than 350 real business examples, cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. And, to give you the most relevant text you can get for your course, you the topics you want, including coverage of popular commercial statistical software programs like Minitab 16 and Excel 2010, along with StatTools and other leading Excel 2010 statistical add-ins.
TRUSTED TEAM OF EXPERT AUTHORS ENSURES THE MOST ACCURATE, PROVEN PRESENTATION. As prominent, respected leaders and active consultants in business and statistics today, authors David R. Anderson, Dennis J. Sweeney, and Thomas A. Williams, now joined by Jeffrey D. Camm and James J. Cochran provide an accurate presentation of statistical concepts you can trust with every edition.
LEADING PROBLEM-SCENARIO APPROACH HELPS STUDENT UNDERSTAND AND APPLY CONCEPTS. A hallmark strength of this text, this unique approach helps students understand statistical techniques within an applications setting. The statistical results provide insights into business decisions and detail how statistics are used within business today to solve problems.
SYSTEMATIC APPROACH EMPHASIZES PROVEN METHODS AND APPLICATIONS. Students first develop a computational foundation and learn the use of techniques before moving to statistical application and interpretation of the value of techniques. Methods Exercises at the end of each section stress computation and use of formulas, while Application Exercises require students to use what they know about statistics to address real-world problems.
USE OF CUMULATIVE STANDARD NORMAL DISTRIBUTION TABLE PREPARES STUDENTS TO WORK WITH STATISTICAL SOFTWARE. To more effectively prepare today’s students to use computer software in statistics, this book incorporates a normal probability table that is consistent with today’s statistical software. This cumulative normal probability table also makes it easier to compute p-values for hypothesis testing.
SIMPLIFIED INTRODUCTION TO P-VALUES CLARIFIES UNDERSTANDING FOR STUDENTS. As in the previous edition, this edition emphasizes the use of p-values as the preferred approach to hypothesis testing. To further clarify the introduction of this concept for students, the authors now separate a simplified conceptual definition of p-values from operational definitions that clarify how the p-value is computed for a lower-tail test, an upper-tail test, and a two-tail test.
STUDENTS LEARN TO USE SOFTWARE TO COMPUTE P-VALUES. For your flexibility, an optional appendix clearly demonstrates how to use MINITAB and Excel to compute p-values associated with z, t, and F test statistics. This coverage is particularly helpful when discussing hypothesis testing (Chs. 9-16).
Descriptive Statistics--Chapters 2 and 3. We have significantly revised these chapters to incorporate new material on data visualization, best practices, and much more. Chapter 2 has been reorganized to include new material on side-by-side and stacked bar charts, and a new section has been added on data visualization and best practices I creating effective displays. Chapter 3 now includes coverage of the geometric mean in the section on measures of location. The geometric mean has many applications in the computation of growth rates for financial assets, annual percentage rates, and so on. Chapter 3 also includes a new section on data dashboards and how summary statistics can be incorporated to enhance their effectiveness.
Discrete Probability Distributions--Chapter 5. The introductory material in this chapter has been revised to better explain the role of probability distributions and to show how the material on assigning probabilities in Chapter 4 can be used to develop discrete probability distributions. We point out that the empirical discrete probability distribution is developed by using the relative frequency method to assign probabilities. At the request of many users, we have added a new Section 5.4 that covers bivariate discrete distributions and financial applications. We show how financial portfolios can be constructed and analyzed using these distributions.
Chapter 12--Comparing Multiple Proportions, Tests of Independence, and Goodness of Fit. This chapter has undergone a major revision. We have added a new section on testing the equality of three or more population proportions. This section includes a procedure for making multiple comparison tests between all pairs of population proportions. The section on the test of independence has been rewritten to clarify that the test concerns the independence of two categorical variables. Revised appendixes with step-by-step instructions for Minitab, Excel, and StatTools are included.
New Case Problems. We have added 8 new case problems to this edition; the total number of cases is 31. Three new descriptive statistics cases have been added to chapters 2 and 3. Five new case problems involving regression appear in Chapters 14, 15, and 16. These case problems provide students with the opportunity to analyze larger data sets and prepare managerial reports based on the results of their analysis.
New Statistics in Practice Applications. Each chapter begins with a Statistics in Practice vignette that describes an application of the statistical methodology to be covered in the chapter. New to this edition is a Statistics in Practice for Chapter 2 describing the use of data dashboards and data visualization at the Cincinnati Zoo and Botanical Garden. We have also added a Statistics i Practice to Chapter 4 describing how a NASA team used probability to assist in the rescue of 33 Chilean miners trapped by a cave-in.
New Examples and Exercises based on Real Data. We continue to make a significant effort to update our text examples and exercises with the most current real data and referenced sources of statistical information. In this edition, we have added approximately 180 new examples and exercises based on real data and referenced sources. Using data from sources also used by The Wall Street Journal, USA Today, Barron's, and others, we have drawn from actual studies to develop explanations and to create exercises that demonstrate the many uses of statistics in business and economics. We believe that the use of real data helps generate more student interest in the material and enables the student to learn about both the statistical methodology and its application. The twelfth edition contains over 350 examples and exercises based on real data.

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