Essential Statistics, Regression, and Econometrics, Second Edition, is innovative in its focus on preparing students for regression/econometrics, and in its extended emphasis on statistical reasoning, real data, pitfalls in data analysis, and modeling issues. This book is uncommonly approachable and easy to use, with extensive word problems that emphasize intuition and understanding. Too many students mistakenly believe that statistics courses are too abstract, mathematical, and tedious to be useful or interesting. To demonstrate the power, elegance, and even beauty of statistical reasoning, this book provides hundreds of new and updated interesting and relevant examples, and discusses not only the uses but also the abuses of statistics. The examples are drawn from many areas to show that statistical reasoning is not an irrelevant abstraction, but an important part of everyday life. Includes hundreds of updated and new, real-world examples to engage students in the meaning and impact of statistics Focuses on essential information to enable students to develop their own statistical reasoning Ideal for one-quarter or one-semester courses taught in economics, business, finance, politics, sociology, and psychology departments, as well as in law and medical schools Accompanied by an ancillary website with an instructors solutions manual, student solutions manual and supplementing chapters

Essential Statistics, Regression, and Econometrics provides students with a readable, deep understanding of the key statistical topics they need to understand in an econometrics course. It is innovative in its focus, including real data, pitfalls in data analysis, and modeling issues (including functional forms, causality, and instrumental variables). This book is unusually readable and non-intimidating, with extensive word problems that emphasize intuition and understanding. Exercises range from easy to challenging and the examples are substantial and real, to help the students remember the technique better. It offers readable exposition and exceptional exercises/examples that students can relate to. It focuses on key methods for econometrics students without including unnecessary topics. It covers data analysis not covered in other texts. It includes ideal presentation of material (topic order) for econometrics .

Essential Statistics for Economics, Business and Management assumes no prior knowledge of statistics. It will also be highly relevant for the statistics component of courses in quantitative methods. The style of the book is similar to that of the highly successful Essential Mathematics for Economics and Business by Teresa Bradley and Paul Patton, with many worked examples integrated throughout. Emphasis is placed on verbalising concepts, problems and results of statistical analysis. This will help students learn how to start a problem, complete the calculations, and report the results in a way that makes sense to a non-statistician. Each concept is introduced with a brief but plausible explanation followed by Worked Examples. The Worked Examples will provide students with the necessary practice that they need in order to succeed at the subject. Emphasis is also placed on ?learning through doing? problems. Excel is used to encourage students in doing problems and to enhance understanding (with links to datasets online). Minitab printouts are also included in the text. Skills Development Exercises with brief solutions are included within the chapters, and Progress Exercises on theory and applications are provided at the end of each chapter. Solutions to all the worked examples and progress exercises are available as an appendix. Web-based supplementary materials will be provided for lecturers adopting the text, including additonal exercises and solutions, excel datasets and exercises, powerpoint slides with key formula, figures and tables. Students can access an online glossary and weblinks.

Combines technique with application using real data sets. The core of the book (Chapters 1-13) covers the basic statistical concepts necessary for econometrics with an emphasis on regression analysis. Part V is a treatment of advanced econometrics theory.

With the rise of "big data," there is an increasing demand to learn the skills needed to undertake sound quantitative analysis without requiring students to spend too much time on high-level math and proofs. This book provides an efficient alternative approach, with more time devoted to the practical aspects of regression analysis and how to recognize the most common pitfalls. By doing so, the book will better prepare readers for conducting, interpreting, and assessing regression analyses, while simultaneously making the material simpler and more enjoyable to learn. Logical and practical in approach, Regression Analysis teaches: (1) the tools for conducting regressions; (2) the concepts needed to design optimal regression models (based on avoiding the pitfalls); and (3) the proper interpretations of regressions. Furthermore, this book emphasizes honesty in research, with a prevalent lesson being that statistical significance is not the goal of research. This book is an ideal introduction to regression analysis for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better understand what regressions do, what their limitations are, and what they can tell us. This will be the most engaging book on regression analysis (or Econometrics) you will ever read! A collection of author-created supplementary videos are available at: https://www.youtube.com/channel/UCenm3BWqQyXA2JRKB_QXGyw

A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.

This book provides the most comprehensive and up-to-date account of regression methods to explain the frequency of events.