Learn how to make informed decisions through statistical reasoning! Using a qualitative approach to introduce statistical reasoning, The Numerate Leader: How to Pull Game-Changing Insights from ...Statistical Data is a cutting-edge book that helps the reader extract information from unfamiliar data sets. Combining introductory statistics with a few ideas from the philosophy of science, this work helps generalists find patterns that may be expected to recur in the future. Identifying one or two such relationships can be a game-changer for the reader and their employer or client. Thomas A. King's revelatory writing is easy to understand and conversational in tone. King makes the complex, tedious topics that you studied in the classroom but likely didn't yet understand easily comprehensible. Historical examples and humorous anecdotes illuminate technical concepts so that readers may pull insights from data sets and then explain conclusions reached through effective storytelling. What's more, the book is fun to read. A natural teacher, King emphasizes that complex software is unnecessary for success in this field. Readers, however, will find: Real-life examples that help put statistical concepts into an understandable context A glossary of important statistical terms and their use An appendix detailing ten math facts numerate people should know Perfect for undergraduate and graduate students entering advanced data analytics courses, as well as data analysts and c-suite executives just starting out, The Numerate Leader is key in helping develop the skills to identify provisional relationships between disparate data sets and then assess the significance of conclusions reached.
This book will provide a comprehensive overview of business analytics, for those who have either a technical background (quantitative methods) or a practitioner business background. Business ...analytics, in the context of the 4th Industrial Revolution, is the "new normal" for businesses that operate in this digital age. This book provides a comprehensive primer and overview of the field (and related fields such as Business Intelligence and Data Science). It will discuss the field as it applies to financial institutions, with some minor departures to other industries. Readers will gain understanding and insight into the field of data science, including traditional as well as emerging techniques. Further, many chapters are dedicated to the establishment of a data-driven team - from executive buy-in and corporate governance to managing and quantifying the return of data-driven projects.
Das Lehr- & Lernbuch für Wirtschaftswissenschaftler mit Aufgaben und Lösungen. Anhand von Praxisbeispielen aus der BWL und zahlreichen Anwendungen werden alle Inhalte vermittelt, die in den ...Pflichtvorlesungen zur Mathematik für Wirtschaftsinformatiker und Betriebswirtschaftler thematisiert werden, wie Finanzmathematik, Extremwertberechnung und Lineare Algebra. Um dieses Wissen verständlich zu vermitteln, werden die gängigen Methoden vom Autor ausführlich beleuchtet, damit der Lernende in die Lage versetzt wird, die vorgestellten Modelle zu analysieren, weiterzuentwickeln und an die eigenen Erfordernisse anzupassen. Die Verständnisfragen und Aufgaben mit Lösungen zu jedem Kapitel, erleichtern es dem Studierenden, die eigenen Fortschritte zu überprüfen und Wissenslücken aufzuspüren. Klausuraufgaben mit angegebener Gewichtung helfen die Prüfungssituation zu simulieren. Abgerundet wird das Lehrbuch durch ein Repetitorium Schulmathematik, durch das die wichtigsten Grundlagen aufgefrischt werden können.
Learn how to make informed decisions through statistical reasoning! Using a qualitative approach to introduce statistical reasoning, The Numerate Leader: How to Pull Game-Changing Insights from ...Statistical Data is a cutting-edge book that helps the reader extract information from unfamiliar data sets. Combining introductory statistics with a few ideas from the philosophy of science, this work helps generalists find patterns that may be expected to recur in the future. Identifying one or two such relationships can be a game-changer for the reader and their employer or client. Thomas A. King's revelatory writing is easy to understand and conversational in tone. King makes the complex, tedious topics that you studied in the classroom-but likely didn't yet understand-easily comprehensible. Historical examples and humorous anecdotes illuminate technical concepts so that readers may pull insights from data sets and then explain conclusions reached through effective storytelling. What's more, the book is fun to read. A natural teacher, King emphasizes that complex software is unnecessary for success in this field. Readers, however, will find: Real-life examples that help put statistical concepts into an understandable context A glossary of important statistical terms and their use An appendix detailing ten math facts numerate people should know Perfect for undergraduate and graduate students entering advanced data analytics courses, as well as data analysts and c-suite executives just starting out, The Numerate Leader is key in helping develop the skills to identify provisional relationships between disparate data sets and then assess the significance of conclusions reached.
Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. ...To keep the book practical and applied, the authors feature a running case using a global airline business's customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.
Written for the non-mathematician and free of unexplained technical jargon, Applied Statistics: Business and Management Research provides a user-friendly introduction to the field of applied ...statistics and data analysis. Featuring step-by-step explanations of how to carry out successful quantitative research, and supported by examples from IBM® SPSS® Statistics, this textbook is an essential resource for students and researchers of business and management. A range of online resources for both students and lecturers, including a teaching guide, PowerPoint slides and datasets, are available via the companion website. Andrew R. Timming is Professor of Human Resource Management and Deputy Dean Research & Innovation in the School of Management at RMIT University, Australia.
This book was written for those who want basic understanding of how to use analytics in the business world without all the details of statistical theory. The focus is on providing clear word ...descriptions and step-by-step Excel instructions, rather than including lots of x's and y's everywhere. We have specifically avoided including a lot of technical information. This book was written for the managers and students who may need a quick refresher on how to complete Excel analysis without having to read pages of technical explanations. We have aimed at concisely defining the key concepts and providing simple descriptions and explanations on how to use them.
Statistical Analysis of Management Data provides a comprehensive approach to multivariate statistical analyses that are important for researchers in all fields of management, including finance, ...production, accounting, marketing, strategy, technology, and human resources. This book is especially designed to provide doctoral students with a theoretical knowledge of the concepts underlying the most important multivariate techniques and an overview of actual applications. It offers a clear, succinct exposition of each technique with emphasis on when each technique is appropriate and how to use it. This second edition, fully revised, updated, and expanded, reflects the most current evolution in the methods for data analysis in management and the social sciences. In particular, it places a greater emphasis on measurement models, and includes new chapters and sections on: confirmatory factor analysis canonical correlation analysis cluster analysis analysis of covariance structure multi-group confirmatory factor analysis and analysis of covariance structures. Featuring numerous examples, the book may serve as an advanced text or as a resource for applied researchers in industry who want to understand the foundations of the methods and to learn how they can be applied using widely available statistical software. TOC:1: Introduction.- 2: Multivariate Normal Distribution.- 3: Measurement Theory: Reliability and Factor Analysis.- 4: Multiple Regression with a Single Dependent Variable.- 5: System of Equations.- 6: Categorial Dependent Variables.- 7: Rank Ordered Data.- 8: Error in Variables - Analysis of Covariance Structure.- 9: Analyses of Similarity and Preference Data.- Appendices: A: Rules in Matrix Algebra.- B: Statistical Tables.- C: Description of Data Sets.
This book is intended to be primarily a supplemental text that can be used to integrate the use of computer packages into introductory business statistics and quantitative methods courses, ...demonstrating how computer packages can be used to solve statistical and operational research problems.
Introductory Business Statistics is designed to meet the scope and sequence requirements of the one-semester statistics course for business, economics, and related majors. Core statistical concepts ...and skills have been augmented with practical business examples, scenarios, and exercises. The result is a meaningful understanding of the discipline, which will serve students in their business careers and real-world experiences. Alexander Holmes, The University of Oklahoma; Barbara Illowsky, DeAnza College; Susan Dean, DeAnza College; Kevin Hadley, Analyst, Federal Reserve Bank of Kansas City;
