Business Statistics: Communicating with Numbers ISE - Sanjiv Jaggia

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Résumé :
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
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Biographie:
Sanjiv Jaggia is a professor of economics and finance at California Polytechnic State University in San Luis Obispo. Dr. Jaggia holds a Ph.D. from Indiana University and is a Chartered Financial Analyst (CFA?). He enjoys research in statistics and data analytics applied to a wide range of business disciplines. Dr. Jaggia has published numerous papers in leading academic journals and has co-authored three successful textbooks, two in business statistics and one in business analytics. His ability to communicate in the classroom has been acknowledged by several teaching awards. Dr. Jaggia resides in San Luis Obispo with his wife and daughter. In his spare time, he enjoys cooking, hiking, and listening to a wide range of music. ...

Sommaire:
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....