Business Case Analysis With R
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Business Case Analysis With R
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Author : Robert D. Brown III
language : en
Publisher: Apress
Release Date : 2018-03-01
Business Case Analysis With R written by Robert D. Brown III and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-01 with Computers categories.
This tutorial teaches you how to use the statistical programming language R to develop a business case simulation and analysis. It presents a methodology for conducting business case analysis that minimizes decision delay by focusing stakeholders on what matters most and suggests pathways for minimizing the risk in strategic and capital allocation decisions. Business case analysis, often conducted in spreadsheets, exposes decision makers to additional risks that arise just from the use of the spreadsheet environment. R has become one of the most widely used tools for reproducible quantitative analysis, and analysts fluent in this language are in high demand. The R language, traditionally used for statistical analysis, provides a more explicit, flexible, and extensible environment than spreadsheets for conducting business case analysis. The main tutorial follows the case in which a chemical manufacturing company considers constructing a chemical reactor and production facility to bring a new compound to market. There are numerous uncertainties and risks involved, including the possibility that a competitor brings a similar product online. The company must determine the value of making the decision to move forward and where they might prioritize their attention to make a more informed and robust decision. While the example used is a chemical company, the analysis structure it presents can be applied to just about any business decision, from IT projects to new product development to commercial real estate. The supporting tutorials include the perspective of the founder of a professional service firm who wants to grow his business and a member of a strategic planning group in a biomedical device company who wants to know how much to budget in order to refine the quality of information about critical uncertainties that might affect the value of a chosen product development pathway. What You’ll Learn Set up a business case abstraction in an influence diagram to communicate the essence of the problem to other stakeholders Model the inherent uncertainties in the problem with Monte Carlo simulation using the R language Communicate the results graphically Draw appropriate insights from the results Develop creative decision strategies for thorough opportunity cost analysis Calculate the value of information on critical uncertainties between competing decision strategies to set the budget for deeper data analysis Construct appropriate information to satisfy the parameters for the Monte Carlo simulation when little or no empirical data are available Who This Book Is For Financial analysts, data practitioners, and risk/business professionals; also appropriate for graduate level finance, business, or data science students
Applied Analytics Through Case Studies Using Sas And R
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Author : Deepti Gupta
language : en
Publisher: Apress
Release Date : 2018-08-03
Applied Analytics Through Case Studies Using Sas And R written by Deepti Gupta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-03 with Computers categories.
Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. What You'll Learn Understand analytics and basic data concepts Use an analytical approach to solve Industrial business problems Build predictive model with machine learning techniques Create and apply analytical strategies Who This Book Is For Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.
Business Analytics Using R A Practical Approach
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Author : Umesh R Hodeghatta
language : en
Publisher: Apress
Release Date : 2016-12-27
Business Analytics Using R A Practical Approach written by Umesh R Hodeghatta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-27 with Computers categories.
Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.
Applied Linear Regression For Business Analytics With R
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Author : Daniel P. McGibney
language : en
Publisher: Springer Nature
Release Date : 2023-07-04
Applied Linear Regression For Business Analytics With R written by Daniel P. McGibney and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-04 with Business & Economics categories.
Applied Linear Regression for Business Analytics with R introduces regression analysis to business students using the R programming language with a focus on illustrating and solving real-time, topical problems. Specifically, this book presents modern and relevant case studies from the business world, along with clear and concise explanations of the theory, intuition, hands-on examples, and the coding required to employ regression modeling. Each chapter includes the mathematical formulation and details of regression analysis and provides in-depth practical analysis using the R programming language.
Data Mining With R
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Author : Luis Torgo
language : en
Publisher: CRC Press
Release Date : 2016-11-30
Data Mining With R written by Luis Torgo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-30 with Business & Economics categories.
Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.
Strategic Business Case Analysis
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Author : Christopher Williams
language : en
Publisher: Taylor & Francis
Release Date : 2023-12-07
Strategic Business Case Analysis written by Christopher Williams and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-07 with Business & Economics categories.
This textbook provides students with the skills and techniques necessary to analyse business case studies from a strategic perspective. With career development and impact in mind, the book goes beyond simply listing tools, instead teaching students how to prepare for a major strategic business case analysis project, how to position their analysis on a spectrum from reductionist to holistic approaches, how to critically engage with theory and case data, as well as how to leverage their work after completion. A logical approach is offered, taking the reader through the analysis journey, from preparing to analyse a case study to conducting the analysis and maximising the impact going forwards. A comprehensive analysis task is incorporated, which asks the reader to reflect on a range of case data, understand the choices of analytical positioning and tool selection, and develop an analysis based on this positioning. Further pedagogical features include: Reflective practice exercises at the end of chapters, allowing the student to self-identify areas of strength and weakness as they develop through the process. Worked examples based on cases reproduced in the book, allowing the student to follow the analytical process that the author went through in different analysis modes. Quotes and analysis insights from former students who have previously conducted a strategic business case analysis, aiding reflective practice. As case study analysis continues as a core component of teaching across business schools, this unique text will help to build key skills in advanced undergraduate, postgraduate, MBA, and executive education students conducting strategic business case analysis. Support material includes PowerPoint slides as well as video content.
Business Analytics
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Author : Walter R. Paczkowski
language : en
Publisher: Springer Nature
Release Date : 2022-01-03
Business Analytics written by Walter R. Paczkowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-03 with Business & Economics categories.
This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.
Data Analysis For Business Economics And Policy
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Author : Gábor Békés
language : en
Publisher: Cambridge University Press
Release Date : 2021-05-06
Data Analysis For Business Economics And Policy written by Gábor Békés and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-06 with Business & Economics categories.
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Hbr Guide To Building Your Business Case
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Author : Raymond Sheen
language : en
Publisher: Harvard Business Press
Release Date : 2015
Hbr Guide To Building Your Business Case written by Raymond Sheen and has been published by Harvard Business Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Business & Economics categories.
"You've got a great idea that will increase revenue or productivity--but how do you get approval to make it happen? By building a business case that clearly shows its value. Maybe you struggle to win support for projects because you're not sure what kind of data your stakeholders will trust, or naysayers always seem to shoot your ideas down at the last minute. Or perhaps you're intimidated by analysis and number crunching, so you just take a stab at estimating costs and benefits, with little confidence in your accuracy. To get any idea off the ground at your company you'll have to make a strong case for it. This guide gives you the tools to do that"--
Introduction To R For Business Intelligence
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Author : Jay Gendron
language : en
Publisher: Packt Publishing Ltd
Release Date : 2016-08-26
Introduction To R For Business Intelligence written by Jay Gendron and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-26 with Computers categories.
Learn how to leverage the power of R for Business Intelligence About This Book Use this easy-to-follow guide to leverage the power of R analytics and make your business data more insightful. This highly practical guide teaches you how to develop dashboards that help you make informed decisions using R. Learn the A to Z of working with data for Business Intelligence with the help of this comprehensive guide. Who This Book Is For This book is for data analysts, business analysts, data science professionals or anyone who wants to learn analytic approaches to business problems. Basic familiarity with R is expected. What You Will Learn Extract, clean, and transform data Validate the quality of the data and variables in datasets Learn exploratory data analysis Build regression models Implement popular data-mining algorithms Visualize results using popular graphs Publish the results as a dashboard through Interactive Web Application frameworks In Detail Explore the world of Business Intelligence through the eyes of an analyst working in a successful and growing company. Learn R through use cases supporting different functions within that company. This book provides data-driven and analytically focused approaches to help you answer questions in operations, marketing, and finance. In Part 1, you will learn about extracting data from different sources, cleaning that data, and exploring its structure. In Part 2, you will explore predictive models and cluster analysis for Business Intelligence and analyze financial times series. Finally, in Part 3, you will learn to communicate results with sharp visualizations and interactive, web-based dashboards. After completing the use cases, you will be able to work with business data in the R programming environment and realize how data science helps make informed decisions and develops business strategy. Along the way, you will find helpful tips about R and Business Intelligence. Style and approach This book will take a step-by-step approach and instruct you in how you can achieve Business Intelligence from scratch using R. We will start with extracting data and then move towards exploring, analyzing, and visualizing it. Eventually, you will learn how to create insightful dashboards that help you make informed decisions—and all of this with the help of real-life examples.