Learning Excel for Economics & Business: Statistics Topics

Non-mathematical, hands-on approach with a focus on applications in a variety of disciplines, as statistical methods are discussed using an easily exchangeable data set. Simple language and explanations use concrete and sequential examples.

This book helps you understand the core concepts and principles of business statistics, and how they relate to the business world, similar to an introductory course would. It introduces statistical problems and processes common to the world of global business and economics, and covers topics like probability, sampling techniques and distributions, and drawing conclusions from data.

This textbook gives an overview of statistical methods that have been developed during the last years due to increasing computer use, including random number generators, Monte Carlo methods, Markov Chain Monte Carlo (MCMC) methods, Bootstrap, EM algorithms, SIMEX, variable selection, density estimators, kernel estimators, orthogonal and local polynomial estimators, wavelet estimators, splines, and model assessment.

This book gives readers hands-on understanding of Excel assisted statistical techniques to take effective business decisions. It showcases applications of the tools and techniques of statistics for analyzing business data from the domain of business statistics.

This book offers a comprehensive and readable introduction to modern business and data analytics. It is based on the use of Excel, a tool that virtually all students and professionals have access to. The explanations are focused on understanding the techniques and their proper application, and are supplemented by a wealth of in-chapter and end-of-chapter exercises. In addition to the general statistical methods, the book also includes Monte Carlo simulation and optimization.

This book is a step-by-step, exercise-driven guide for students and practitioners who need to master Excel to solve practical social science problems. If understanding statistics isn't your strongest suit, you are not especially mathematically inclined, or you are wary of computers, this is the right book for you. Excel, a widely available computer program for students and managers, is also an effective teaching and learning tool for quantitative analyses in social science courses. Its powerful computational ability and graphical functions make learning statistics much easier than in years past.

This text is for students studying statistics for advertising and for advertising managers and practitioners who want to learn how to use Excel to solve practical statistics problems in the workplace, whether or not they have taken a course in statistics. This book demonstrates: (1) writing formulas (e.g., confidence interval about the mean, one-group t-test, two-group t-test, correlation) and (2) using Excel's drop-down formula menus (e.g., simple linear regression, multiple correlation and multiple regression, and one-way ANOVA).

This collection of essays examines many of the historical developments in making data visible through charts, graphs, thematic maps, and now interactive displays. The contributors analyze this fascinating history through a variety of critical approaches, including visual rhetoric, visual culture, genre theory, and fully contextualized historical scholarship.

"The book is divided into three Parts: Part One has chapters that introduce data analysis and SPSS; Part Two contains eight chapters on descriptive statistics that begin with frequency tables and go through multiple regression; and Part Three includes six chapters on inferential statistics."