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Essentials of Business Statistics: Communicating with Numbers is a core statistics textbook that sparks student interest and bridges the gap between how statistics is taught and how practitioners think about and apply statistical methods. Throughout the text, the emphasis is on communicating with numbers rather than on number crunching. By incorporating the perspective of professional users, the subject matter is more relevant and the presentation of material more straightforward for students.
KEY FEATURES
1.Integrated Introductory Cases: Realistic introductory cases that students can relate to introduce each chapter topic and form the basis of several examples in the chapters.
2.Writing with Statistics: Interpreting results and conveying information effectively is critical to effective decision making in a business environment. Students are taught how to take the data, apply it, and convey the information in a meaningful way.
3.Unique Coverage of Regression Analysis: Extensive coverage of regression without repetition is an important hallmark of this text.
4.Written as Taught: Topics are presented the way they are taught in class, beginning with the intuition and explanation and concluding with the application.
5.Mechanical and Applied Exercises: Chapter exercises are a well-balanced blend of mechanical, computational-type problems followed by more ambitious, interpretive-type problems.
6.Conceptual Review: At the end of each chapter, there is a conceptual review that provides a more holistic approach to reviewing the material. This section revisits the learning outcomes and provides the most important definitions, interpretations, and formulas.
7.Integration of Microsoft(R) Excel: Students are taught to develop an understanding of the concepts and how to derive the calculation; then Excel is used as a tool to perform the cumbersome calculations. In addition, guidelines for using Minitab, SPSS, and JMP are provided in chapter appendices.
8.Connect Business Statistics: Connect is an online system that gives students the tools they need to be successful in the course. Through guided examples and LearnSmart adaptive study tools, students receive guidance and practice to help them master the topics.
作者簡介
Sanjiv Jaggia
現職：California Polytechnic State University
Alison Kelly
現職：Suffolk University
PART I: INTRODUCTION
Ch1 Statistics and Data
PART II: DESCRIPTIVE STATISTICS
Ch2 Tabular and Graphical Methods
Ch3 Numerical Descriptive Measures
PART III: PROBABILITY AND PROBABILITY DISTRIBUTIONS
Ch4 Introduction to Probability
Ch5 Discrete Probability Distributions
Ch6 Continuous Probability Distributions
PART IV: BASIC INFERENCE
Ch7 Sampling and Sampling Distributions
Ch8 Estimation
Ch9 Hypothesis Testing
Ch10 Comparisons Involving Means
Ch11 Comparisons Involving Proportions
PART V: ADVANCED INFERENCE
Ch12 Basics of Regression Analysis
Ch13 More on Regression Analysis
