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Business Statistics: Communicating with Numbers ISE

5th Edition
1266802509 · 9781266802508
Business Statistics: Communicating with Numbers takes a comprehensive and contemporary approach that aims to bridge the gap between how statistics is taught and applied in the business world. This title not only prepares students in basic statistics… Read More
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PART ONE: INTRODUCTION 
 1 Data and Data Preparation 

PART TWO: DESCRIPTIVE STATISTICS 
 2 Tabular and Graphical Methods 
 3 Numerical Descriptive Measures 

PART THREE: PROBABILITIY AND PROBABILITY DISTRIBUTIONS
 4 Introduction to Probability 
 5 Discrete Probability Distributions 
 6 Continuous Probability Distributions 

PART FOUR: BASIC INFERENCE 
 7 Sampling and Sampling Distributions 
 8 Interval Estimation 
 9 Hypothesis Testing
 10 Statistical Inference Concerning Two Populations 
 11 Statistical Inference Concerning Variance 
 12 Chi-Square Tests 

PART FIVE: ADVANCED INFERENCE 
 13 Analysis of Variance 
 14 Regression Analysis 
 15 Inference with Regression Models 
 16 Regression Models for Nonlinear Relationships 
 17 Regression Models with Dummy Variables 

PART SIX: SUPPLEMENTARTY TOPICS 
 18 Forecasting with Time Series Data 
 19 Returns, Index Numbers, and Inflation 
 20 Nonparametric Tests 

APPENDIX A: Getting Started with R 
APPENDIX B: Tables 
APPENDIX C: Answers to Selected Even-Numbered Exercises 
Business Statistics: Communicating with Numbers takes a comprehensive and contemporary approach that aims to bridge the gap between how statistics is taught and applied in the business world. This title not only prepares students in basic statistics but also gets them excited about further exploration of data analytics. The authors emphasize communicating with numbers rather than number crunching, through relatable case studies with relevant statistical methods and takeaways. This title incorporates timely examples from various fields, reinforces core features from previous editions, uses Excel and R to analyze data and solve problems, and includes new improvements, such as a revised chapter on data visualization, an exclusive chapter on logistic regression, and digital enhancements such as a big data capstone project with algorithmic exercises that span across multiple chapters.
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