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Author: Robert D. Brown III
Publisher: Apress
ISBN: 1484234952
Category : Computers
Languages : en
Pages : 287
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Book Description
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
Author: Robert D. Brown III
Publisher: Apress
ISBN: 1484234952
Category : Computers
Languages : en
Pages : 287
Get Book Here
Book Description
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
Author: Gábor Békés
Publisher: Cambridge University Press
ISBN: 1108483011
Category : Business & Economics
Languages : en
Pages : 741
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Book Description
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.
Author: Umesh R Hodeghatta
Publisher: Apress
ISBN: 1484225147
Category : Computers
Languages : en
Pages : 291
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Book Description
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.
Author: Robert E. Stake
Publisher: Guilford Press
ISBN: 1462512402
Category : Psychology
Languages : en
Pages : 496
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Book Description
Examining situational complexity is a vital part of social and behavioral science research. This engaging text provides an effective process for studying multiple cases--such as sets of teachers, staff development sessions, or clinics operating in different locations--within one complex program. The process also can be used to investigate broadly occurring phenomena without programmatic links, such as leadership or sibling rivalry. Readers learn to design, analyze, and report studies that balance common issues across the group of cases with the unique features and context of each case. Three actual case reports from a transnational early childhood program illustrate the author's approach, and helpful reproducible worksheets facilitate multicase recording and analysis.
Author: Jillian Dawes Farquhar
Publisher: SAGE
ISBN: 1446281205
Category : Business & Economics
Languages : en
Pages : 147
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Book Description
The only case study research textbook written exclusively for students of Business and related disciplines. Using a step-by-step approach, Case Study Research for Business takes you right through the case study research process from research design and data collection using qualitative and quantitative methods, to research analysis, writing up and presenting your work. Key features: - Takes a multidisciplinary approach to case study research design by drawing on research philosophies to improve student understanding of these critical research traditions and hence provide firmer theoretical foundations for their research - Coverage of contemporary topics such as research ethics and access - Packed with practical examples from all areas of business - Pedagogical features include vignettes, exercises and ′cases′ which directly relate to business research Case Study Research for Business will prove a valuable resource for undergraduate, postgraduate and research students of business and related disciplines.
Author: Jay Gendron
Publisher: Packt Publishing Ltd
ISBN: 178528651X
Category : Computers
Languages : en
Pages : 223
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Book Description
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.
Author: Christopher Williams
Publisher: Taylor & Francis
ISBN: 1000997790
Category : Business & Economics
Languages : en
Pages : 223
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Book Description
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.
Author: Kupe Kupersmith
Publisher: John Wiley & Sons
ISBN: 1118510631
Category : Business & Economics
Languages : en
Pages : 387
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Book Description
Your go-to guide on business analysis Business analysis refers to the set of tasks and activities that help companies determine their objectives for meeting certain opportunities or addressing challenges and then help them define solutions to meet those objectives. Those engaged in business analysis are charged with identifying the activities that enable the company to define the business problem or opportunity, define what the solutions looks like, and define how it should behave in the end. As a BA, you lay out the plans for the process ahead. Business Analysis For Dummies is the go to reference on how to make the complex topic of business analysis easy to understand. Whether you are new or have experience with business analysis, this book gives you the tools, techniques, tips and tricks to set your project’s expectations and on the path to success. Offers guidance on how to make an impact in your organization by performing business analysis Shows you the tools and techniques to be an effective business analysis professional Provides a number of examples on how to perform business analysis regardless of your role If you're interested in learning about the tools and techniques used by successful business analysis professionals, Business Analysis For Dummies has you covered.
Author: Roland W. Scholz
Publisher: SAGE
ISBN: 9780761919469
Category : Business & Economics
Languages : en
Pages : 412
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Book Description
In an embedded case study, the starting and end point is the comprehension of the case as a whole in its real-world context. This book bridges the gap between quantitative and qualitative approaches to complex problems when using this methodology.
Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1119013461
Category : Business & Economics
Languages : en
Pages : 388
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Book Description
A complete set of statistical tools for beginning financial analysts from a leading authority Written by one of the leading experts on the topic, An Introduction to Analysis of Financial Data with R explores basic concepts of visualization of financial data. Through a fundamental balance between theory and applications, the book supplies readers with an accessible approach to financial econometric models and their applications to real-world empirical research. The author supplies a hands-on introduction to the analysis of financial data using the freely available R software package and case studies to illustrate actual implementations of the discussed methods. The book begins with the basics of financial data, discussing their summary statistics and related visualization methods. Subsequent chapters explore basic time series analysis and simple econometric models for business, finance, and economics as well as related topics including: Linear time series analysis, with coverage of exponential smoothing for forecasting and methods for model comparison Different approaches to calculating asset volatility and various volatility models High-frequency financial data and simple models for price changes, trading intensity, and realized volatility Quantitative methods for risk management, including value at risk and conditional value at risk Econometric and statistical methods for risk assessment based on extreme value theory and quantile regression Throughout the book, the visual nature of the topic is showcased through graphical representations in R, and two detailed case studies demonstrate the relevance of statistics in finance. A related website features additional data sets and R scripts so readers can create their own simulations and test their comprehension of the presented techniques. An Introduction to Analysis of Financial Data with R is an excellent book for introductory courses on time series and business statistics at the upper-undergraduate and graduate level. The book is also an excellent resource for researchers and practitioners in the fields of business, finance, and economics who would like to enhance their understanding of financial data and today's financial markets.
