Business Statistics: A First Course and CD-ROM, Third Edition - Softcover

Levine, David M.; Krehbiel, Timothy C.; Berenson, Mark L.

Softcover

ISBN 10: 0130782017 ISBN 13: 9780130782014

Publisher: Pearson College Div, 2006

Synopsis

This book covers the concepts and applications of statistics used in the functional areas of business-accounting, marketing, management, economics, and finance. With a strong emphasis on concepts rather than on statistical methods, it shows readers how to properly use statistics to analyze data, demonstrates how computer software is an integral part of this analysis, and provides many exercises, cases and projects to support the learning process. Introduction and Data Collection. Presenting Data in Tables and Charts. Numerical Descriptive Measures. Basic Probability. Probability Distributions. Sampling Distributions and Confidence Intervals. Fundamentals of Hypothesis Testing: One-Sample Tests. Hypothesis Tests for Numerical Data from Two or More Samples. Hypothesis Tests for Categorical Data From Two or More Samples. Simple Linear Regression. Multiple Regression Analysis. Time Series Analysis. Statistical Applications in Quality and Productivity Management. For statisticians.

About this title

From the Back Cover

Key Benefit: Written in a warm and engaging style, this carefully developed, streamlined paperback offers a real-world, analytical approach to learning the basics of business statistics. Key Topics: Clarifying and applying concepts with an extensive amount of real data, the book delves into such areas as: why a manager needs to know about statistics; organizing numerical data; determining the simple linear regression equation; hypothesis-testing methodology, and more. It provides simplified notation that uses words as well as symbols in many formulas, presents early coverage of regression and time series analysis, and highlights sections on Good Data Analysis. Market: For business professionals.

Excerpt. © Reprinted by permission. All rights reserved.

Educational Philosophy

In our many years of teaching introductory statistics courses, we have continually searched for ways to improve the teaching of these courses. Our vision for teaching these introductory business statistics courses has been shaped by active participation in a series of Making Statistics More Effective in Schools of Business, Decision Sciences Institute, and American Statistical Association conferences as well as the reality of serving a diverse group of students at large universities. Over the years, our vision has come to include these principles:

1. Students need a frame of reference when learning statistics, especially since statistics is not their major. That frame of reference for business students should be the functional areas of business—that is, accounting, economics and finance, information systems, management, and marketing. Each statistical topic needs to be presented in an applied context related to at least one of these functional areas.
2. Virtually all the students taking introductory business statistics courses are majoring in areas other than statistics. Introductory courses should focus on underlying principles that nonstatistics majors will find useful.
3. The use of spreadsheet and/or statistical software should be integrated into all aspects of an introductory statistics course. In the workplace, spreadsheet software (and sometimes statistical software) is usually available on a decision maker's desktop. Our teaching approach needs to recognize this reality, and we need to make our courses consistent with the workplace environment.
4. Textbooks that use software must provide enough instructions that students can effectively use the software, without the software (and instruction) dominating the course.
5. The focus in teaching each topic should be on the application of the topic to a functional area of business, the interpretation of results, the presentation of assumptions, the evaluation of the assumptions, and the discussion of what should be done if the assumptions are violated. These points are particularly important in regression and forecasting and in hypothesis testing. Although the illustration of some computations is inevitable, the focus on computations should be minimized.
6. Both classroom examples and homework exercises should relate to actual or realistic data as much as possible. Students should work with data sets, both small and large, and be encouraged to look beyond the statistical analysis of data to the interpretation of results in a managerial context.
7. Introductory courses should avoid an overconcentration on one topic area (such as hypothesis testing) and instead provide breadth of coverage of a variety of statistical topics. This will help students avoid the "I can't see the forest from the trees" syndrome.

New to This Edition

This new third edition of Business Statistics: A First Course has been vastly improved in a number of important areas.

APPLICATIONS

• Updated and improved Using Statistics business scenarios—Each chapter begins with a "Using Statistics" example that shows how statistics can be used in one of the functional areas of business—accounting, finance, information systems, management, or marketing. This scenario (and in some cases an additional scenario) is used throughout the chapter to provide an applied context for the concepts.
• Hundreds of new applied examples and exercises, with data from the Wall Street Journal, USA Today, and other sources have been added to the text.
• Visual Explorations—Provided on the book's accompanying CD-ROM are visual explorations that allow students to interactively explore important statistical concepts in descriptive statistics, probability, the normal distribution, and regression analysis. For example, in descriptive statistics, students observe the effect of changes in the data on the average, median, quartiles, and standard deviation. In sampling distributions, students use simulation to explore the effect of sample size on a probability distribution. With the normal distribution, students see the effect of changes in the mean and standard deviation on the areas under the normal curve. In regression analysis, students have the opportunity of fitting a line and observing how changes in the slope and intercept affect the goodness of fit of the fitted line.
• Using Microsoft Office is a new feature. Located at the ends of Chapters 2 and 3, this feature enables the student to prepare reports by using Microsoft Office tools. These sections show step-by-step how to paste Microsoft Excel tables and charts into a Microsoft Word document and how to prepare PowerPoint presentations.

EXERCISES

• Answers to most even-numbered exercises are provided at the end of the book.
• Report Writing Exercises allow students to place the results of an analysis in a business context by incorporating Microsoft Office techniques such as pasting Microsoft Excel tables and charts into a Microsoft Word document and PowerPoint presentation.
• Internet Exercises, located on the book's Web site (www.prenhall.com/levine), allow students to explore data sources that are available on the World Wide Web.
• Case Studies and Team Projects—Detailed case studies are included at the ends of many chapters. The Springville Herald case is included at the end of most chapters as an integrating theme. A team project relating to mutual funds is also included at the end of most chapters as an integrating theme.

TEXT DESIGN

• A new streamlined design that uses full-color text.

SOFTWARE

• Emphasis on data analysis and interpretation of computer output—We take the position that the use of computer software (Microsoft Excel or a statistical software package such as Minitab or SPSS®) is an integral part of learning statistics. Our focus emphasizes analyzing data, interpreting the output from Microsoft Excel or Minitab or SPSS®, and explaining how to use this software while reducing emphasis on doing computations. Therefore, we have added a great deal of computer output and integrated this output into the fabric of the text. For example, in the coverage of tables and charts in Chapter 2, the focus is on the interpretation of various charts, not on their construction by hand. In our coverage of hypothesis testing in Chapters 7 through 9, extensive computer output has been included so that the p-value approach can be used. In our coverage of simple linear regression in Chapter 10, it is assumed that Microsoft Excel, Minitab, or SPSS® will be used and, thus, the focus is on the interpretation of the output and not on hand calculations (which have been placed in a separate section of the chapter).
• PHStat2 is Prentice Hall's Excel add-in, which provides a custom menu of topics that supplement the Data Analysis Tool of Microsoft Excel. Using Excel and PHStat2, the user is able to perform statistical analysis for virtually all the topics that would be covered in a business statistics course at the introductory level. PHStat2, an updated version of PHStat, includes new features such as histograms and polygons and a help system.
• End-of-chapter appendices on Microsoft Excel, Minitab, and SPSS®, with screen shots of dialog boxes, provide easy-to-follow instructions.

CONTENT CHANGES IN THE THIRD EDITION

• Chapter 1 ("Introduction and Data Collection") provides explanation of how to obtain data from the World Wide Web and contains additional chapter review problems accessing the World Wide Web.
• Chapter 2 ("Presenting Data in Tables and Charts") contains an updated "Using Statistics" example, new graphical excellence examples, a section on the scatter diagram, and a section on placing Microsoft Excel worksheet data and charts into Microsoft Word documents.
• Chapter 3 ("Descriptive Statistics") contains an updated "Using Statistics" exampt4t, additional integration of Excel, Minitab, and SPSS(r) output, coverage of the correlation coefficient, coverage of the geometric mean (which is important for finance students), a Visual Explorations module for descriptive statistics, and placing Microsoft Excel worksheet data and charts in PowerPoint presentations.
• Chapter 4 ("Basic Probability") includes an appendix on PHStat2.
• Chapter 5 ("Probability Distributions") moves covariance so that it follows expected value, uses an example with a negative covariance, adds a second "Using Statistics" scenario involving an Internet company, uses only the cumulative normal table, integrates Excel and Minitab output into the normal distribution section, and contains a Visual Exploration module for the normal distribution.
• Chapter 6 ("Sampling Distributions and Confidence Interval Estimation") streamlines the introductory section and contains a Visual Explorations module for sampling distributions.
• Chapter 7 ("Fundamentals of Hypothesis Testing: One-Sample Tests") adds computer output to all sections and combines sections so that the p-value approach is not in a separate section.
• Chapter 8 ("Hypothesis Tests for Numerical Data from Two or More Samples") changes the "Using Statistics" example to one related to marketing and provides additional emphasis on p-values.
• Chapter 9 ("Hypothesis Tests for Categorical Data from Two or More Samples") adds the confidence interval estimate for the difference between two proportions.
• Chapter 10 ("Simple Linear Regression") adds additional coverage of PHStat2 and contains a Visual Explorations module on regression.
• Chapter 11 ("Multiple Regression") adds a section on transformations and adds new PHStat2 features to the sections on stepwise regression and confidence intervals for the mean respo...

Edition details

• Publisher: Pearson College Div
• Publication date: 2006
• ISBN 10: 0130782017
• ISBN 13: 9780130782014
• Binding: Paperback
• Language: English
• Edition number: 3
• Number of pages: 640