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Qué busca el headhunter: Lo que saben los cazatalentos y cómo emplearlo a tu favor
by Arancha RuizEste libro explica cómo funciona el negocio del headhunter y cómo el candidato puede aprovechar todo este conocimiento para su progreso profesional. El cazatalentos tiene un halo misterioso. ¿Qué hay detrás de ese aparente enigma? El elemento diferencial de un headhunter es la creación y el mantenimiento de su red de contactos y la hábil gestión de la información que posee. Conocer esta información que puede ser de enorme utilidad para afrontar un proceso activo de búsqueda de un nuevo empleo. Qué busca el headhunter es un libro práctico con el que aprenderás:- Qué tipo de talento busca un headhunter.- Qué rol asumes en el proceso y cómo fortalecer tu posición como candidato.- Cómo funciona el networking del cazatalentos.- Dónde irá a buscar tu talento un headhunter: cómo asegurarte de que te encuentre.- Cómo dominar el discurso para ser identificado como un candidato valioso.- Cuáles son los momentos críticos del proceso y cómo no fallar en ellos. El negocio de la selección de ejecutivos tiene una dinámica particular. Cuando conozcas los roles de la empresa, del headhunter y del candidato comprenderás quién es realmente el cliente y qué puedes esperar.
Qué hace la gente exitosa antes del desayuno. Una guía práctica para organizar tus mañanas y tu vida: Una guía práctica para organizar tus mañanas y tu vida
by Gary VaynerchuyIncrementa tu potencial y liderazgo en los negocios y en tu vida, organizando tus metas durante la mañana. Tips y herramientas prácticas que utilizan las personas exitosas para aprovechar sus desayunos y lograr todo lo que se proponen.Las mañanas son la clave para tomar el control de tus horarios. Si las usas sabiamente, podrás construir hábitos que te permitan llevar una vida más feliz y más productiva.Sobre la base de anécdotas de la vida real e investigación científica que muestra por qué las primeras horas del día son tan importantes, Laura Vanderkam revela cómo las personas exitosas usan las mañanas para realizar las cosas que, a menudo, son imposibles de hacer más tarde en el día.En sólo 5 pasos aprenderás cómo sacar el máximo provecho a todas tus mañanas: Usa en forma provechosa el tiempo.Descubre en cada mañana el día perfecto.Realiza una logística efectiva. Crea hábitos positivos.Trabaja con objetivos definidos y deadlines.Qué hace la gente exitosa antes del desayuno es una guía divertida y práctica que te inspirará a repensar tu rutina matutina y poner en marcha tu vida antes de que el día haya comenzado.
Qué hace la gente exitosa con su tiempo libre: ¡Siéntete menos ocupado y logra más!
by Laura Vanderkam¡Disfruta de la vida sin importar cuán ocupado estés! La mayoría de nosotros nos sentimos constantemente ajetreados, inseguros de cómo escapar de la sensación de opresión por tantas cosas que hacer. Piénsalo: ¿por qué no has corrido esos 10 km o leído ese libro en tu buró? Laura Vanderkam, autora del bestseller Qué hace la gente exitosa antes del desayuno, asegura que con los hábitos correctos puedes vivir de manera eficiente y efectiva y aun así percibir el tiempo de forma abundante. La autora establece 7 principios para aprovecharlo: 1. Atiende tu jardín. 2. Haz que la vida sea memorable. 3. No llenes el tiempo. 4. Permanece. 5. Invierte en tu felicidad. 6. Déjalo ir. 7. Vale la pena invertir tu tiempo en otros. Las estrategias en este libro no sólo te ayudarán a organizar tu vida sino que llevarán tu carrera, tus relaciones y tu felicidad al siguiente nivel.
Qué harías si no tuvieras miedo: Claves para reinventarte profesionalmente y prosperar en la nueva era
by Borja VilasecaEs hora de vencer los miedos que nos impiden seguir a nuestro corazón, y emprender una función profesional útil, creativa y con sentido. Si quieres conocer el mercado laboral que se avecina, léete este libro. Si quieres sobrevivir y prosperar en la nueva era, ponlo en práctica. El mundo para el que fuimos educados está dejando de existir. Las reglas del juego económico han cambiado. Somos una generación de transición entre dos eras: la industrial/analógica y la del conocimiento/digital. De ahí que no nos quede más remedio que reinventarnos, cuestionando las viejas creencias y consignas con las que fuimos condicionados. En caso de no hacerlo, pronto quedaremos obsoletos y nos quedaremos fuera del mercado. Lo más difícil consiste en vencer el miedo al cambio. Irónicamente, evitar el riesgo y permanecer en nuestra zona de comodidad es lo más arriesgado quepodemos hacer. Ha llegado la hora de saltar al vacío y emprender la travesía por el desierto, descubriendo de qué manera podemos desarrollar una profesión útil, creativa y con sentido que aporte mucho valor añadido. Solo así lograremos gozar de ingresos económicos abundantes y recurrentes en esta nueva era. «Quién quiere encontrará un medio; quién no, una excusa.» PROVERBIO ÁRABE
R o Curic : Cayal Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R o Curic : DDI Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R o Curic : GARC Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R o Curic : IFC Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R o Curic : ONE Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R o Curic : Verdes Juntos Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R o Curic : Went che Role Material
by Kathleen L. McGinn Katherine Chen Julian J. Zlatev Shaaref ShahCase
R Data Analysis without Programming
by David W. GerbingThis book prepares readers to analyze data and interpret statistical results using R more quickly than other texts. R is a challenging program to learn because code must be created to get started. To alleviate that challenge, Professor Gerbing developed lessR. LessR extensions remove the need to program. By introducing R through less R, readers learn how to organize data for analysis, read the data into R, and produce output without performing numerous functions and programming exercises first. With lessR, readers can select the necessary procedure and change the relevant variables without programming. The text reviews basic statistical procedures with the lessR enhancements added to the standard R environment. Through the use of lessR, R becomes immediately accessible to the novice user and easier to use for the experienced user. Highlights of the book include: Quick Starts that introduce readers to the concepts and commands reviewed in the chapters. Margin notes that highlight,define,illustrate,and cross-reference the key concepts.When readers encounter a term previously discussed, the margin notes identify the page number to the initial introduction. Scenarios that highlight the use of a specific analysis followed by the corresponding R/lessR input and an interpretation of the resulting output. Numerous examples of output from psychology, business, education, and other social sciences, that demonstrate how to interpret results. Two data sets provided on the website and analyzed multiple times in the book, provide continuity throughout. End of chapter worked problems help readers test their understanding of the concepts. A website at www.lessRstats.com that features the lessR program, the book’s data sets referenced in standard text and SPSS formats so readers can practice using R/lessR by working through the text examples and worked problems, PDF slides for each chapter, solutions to the book’s worked problems, links to R/lessR videos to help readers better understand the program, and more. An ideal supplement for graduate or advanced undergraduate courses in statistics, research methods, or any course in which R is used, taught in departments of psychology, business, education, and other social and health sciences, this book is also appreciated by researchers interested in using R for their data analysis. Prerequisites include basic statistical knowledge. Knowledge of R is not assumed.
R Data Visualization Cookbook
by Atmajitsinh GohilIf you are a data journalist, academician, student or freelance designer who wants to learn about data visualization, this book is for you. Basic knowledge of R programming is expected.
R For College Mathematics and Statistics
by Thomas PfaffR for College Mathematics and Statistics encourages the use of R in mathematics and statistics courses. Instructors are no longer limited to ``nice'' functions in calculus classes. They can require reports and homework with graphs. They can do simulations and experiments. R can be useful for student projects, for creating graphics for teaching, as well as for scholarly work. This book presents ways R, which is freely available, can enhance the teaching of mathematics and statistics. <p><p> R has the potential to help students learn mathematics due to the need for precision, understanding of symbols and functions, and the logical nature of code. Moreover, the text provides students the opportunity for experimenting with concepts in any mathematics course.
R For Marketing Research and Analytics (Use R!)
by Chris Chapman Elea McDonnell FeitThe 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R for marketing research. This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis.Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.The 2nd edition increases the book’s utility for students and instructors with the inclusion of exercises and classroom slides. At the same time, it retains all of the features that make it a vital resource for practitioners: non-mathematical exposition, examples modeled on real world marketing problems, intuitive guidance on research methods, and immediately applicable code.
R Guide for Introductory Econometrics for Finance
by Chris BrooksThis free software guide for R with freely downloadable datasets brings the econometric techniques to life, showing readers how to implement the approaches presented in Introductory Econometrics for Finance using this highly popular software package. Designed to be used alongside the main textbook, the guide will give readers the confidence and skills to estimate and interpret their own models while the textbook will ensure that they have a thorough understanding of the conceptual underpinnings.
R Markdown Cookbook (Chapman & Hall/CRC The R Series)
by Yihui Xie Christophe Dervieux Emily RiedererThis new book written by the developers of R Markdown is an essential reference that will help users learn and make full use of the software. Those new to R Markdown will appreciate the short, practical examples that address the most common issues users encounter. Frequent users will also benefit from the wide ranging tips and tricks that expose ‘hidden’ features, support customization and demonstrate the many new and varied applications of the software. After reading this book users will learn how to: Enhance your R Markdown content with diagrams, citations, and dynamically generated text Streamline your workflow with child documents, code chunk references, and caching Control the formatting and layout with Pandoc markdown syntax or by writing custom HTML and LaTeX templates Utilize chunk options and hooks to fine-tune how your code is processed Switch between different language engineers to seamlessly incorporate python, D3, and more into your analysis
R Programming and Its Applications in Financial Mathematics
by Shuichi Ohsaki Jori Ruppert-Felsot Daisuke YoshikawaThis book provides an introduction to R programming and a summary of financial mathematics. <P><P>It is not always easy for graduate students to grasp an overview of the theory of finance in an abstract form. For newcomers to the finance industry, it is not always obvious how to apply the abstract theory to the real financial data they encounter. Introducing finance theory alongside numerical applications makes it easier to grasp the subject. <P><P>Popular programming languages like C++, which are used in many financial applications are meant for general-purpose requirements. They are good for implementing large-scale distributed systems for simultaneously valuing many financial contracts, but they are not as suitable for small-scale ad-hoc analysis or exploration of financial data. The R programming language overcomes this problem. R can be used for numerical applications including statistical analysis, time series analysis, numerical methods for pricing financial contracts, etc. <P><P>This book provides an overview of financial mathematics with numerous examples numerically illustrated using the R programming language.
R for Business Analytics
by A OhriR for Business Analytics looks at some of the most common tasks performed by business analysts and helps the user navigate the wealth of information in R and its 4000 packages. With this information the reader can select the packages that can help process the analytical tasks with minimum effort and maximum usefulness. The use of Graphical User Interfaces (GUI) is emphasized in this book to further cut down and bend the famous learning curve in learning R. This book is aimed to help you kick-start with analytics including chapters on data visualization, code examples on web analytics and social media analytics, clustering, regression models, text mining, data mining models and forecasting. The book tries to expose the reader to a breadth of business analytics topics without burying the user in needless depth. The included references and links allow the reader to pursue business analytics topics. This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy. The book utilizes Albert Einstein's famous remarks on making things as simple as possible, but no simpler. This book will blow the last remaining doubts in your mind about using R in your business environment. Even non-technical users will enjoy the easy-to-use examples. The interviews with creators and corporate users of R make the book very readable. The author firmly believes Isaac Asimov was a better writer in spreading science than any textbook or journal author.
R for Marketing Research and Analytics
by Chris Chapman Elea Mcdonnell FeitThis book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.
R for Programmers: Quantitative Investment Applications
by Dan ZhangAfter the fundamental volume and the advanced technique volume, this volume focuses on R applications in the quantitative investment area. Quantitative investment has been hot for some years, and there are more and more startups working on it, combined with many other internet communities and business models. R is widely used in this area, and can be a very powerful tool. The author introduces R applications with cases from his own startup, covering topics like portfolio optimization and risk management.
R for the Rest of Us: A Statistics-Free Introduction
by David KeyesLearn how to use R for everything from workload automation and creating online reports, to interpreting data, map making, and more.Written by the founder of a very popular online training platform for the R programming language!The R programming language is a remarkably powerful tool for data analysis and visualization, but its steep learning curve can be intimidating for some. If you just want to automate repetitive tasks or visualize your data, without the need for complex math, R for the Rest of Us is for you.Inside you&’ll find a crash course in R, a quick tour of the RStudio programming environment, and a collection of real-world applications that you can put to use right away. You&’ll learn how to create informative visualizations, streamline report generation, and develop interactive websites—whether you&’re a seasoned R user or have never written a line of R code.You&’ll also learn how to:• Manipulate, clean, and parse your data with tidyverse packages like dplyr and tidyr to make data science operations more user-friendly• Create stunning and customized plots, graphs, and charts with ggplot2 to effectively communicate your data insights• Import geospatial data and write code to produce visually appealing maps automatically• Generate dynamic reports, presentations, and interactive websites with R Markdown and Quarto that seamlessly integrate code, text, and graphics• Develop custom functions and packages tailored to your specific needs, allowing you to extend R&’s functionality and automate complex tasksUnlock a treasure trove of techniques to transform the way you work. With R for the Rest of Us, you&’ll discover the power of R to get stuff done. No advanced statistics degree required.
R&D Decisions: Strategy Policy and Innovations (Routledge Research in Strategic Management)
by John Hassard Alice Belcher Stephen J. ProcterR&D Decisions, Strategy, Policy and Innovations explores how research and development decisions affect all of us. They are linked inextricably to the performance of firms and of economics as a whole. Their importance means that they are of concern to a large number of practitioners, policy-makers and researchers. This book demonstrates the range of issues and perspectives which R&D can encompass and at the same time brings out the elements which unite them. The papers in this book are organized into three main sections: * Strategy and Organization explores the importance of R&D and of the structures and strategies of individual organizations. The emerging 'core competence paradigm' is especially noted. * Policy and Performance looks at what new thinking on R&D more generally implies for government policy and the performance of industries, regions and economies. * Disclosure and the Market examines issues raised by changing regulations on the disclosure of R&D expenditure.
R&D Management
by K. B. AkhileshThis book contributes towards the integration of the R&D function with regard to societies, nations, industries and organizations, as well as to leaders within organizations. It covers the management aspects and approaches to R&D management and provides information on the major contexts of R&D such as in production, HR, marketing and finance - functions that are essential to attracting, developing and retaining scientific manpower. The book further elaborates on organizations' human strategic prospectives. It also suggests various types of practices to help organizations achieve their objectives and analyzes how R&D can contribute to technology, innovation and science to improve organizations' productivity. In closing, it discusses some of the challenges faced by developing countries and presents R&D management from a global perspective.
R&D Management Practices and Innovation: Evidence from a Firm Survey (SpringerBriefs in Economics)
by Arito Ono Shoko HanedaThis Open Access book provides a detailed account of firms’ research and development (R&D) management practices, and whether and how R&D management practices are associated with the success and the nature (explorative or exploitive) of innovation, using a unique survey of firms in Japan. While there is wide agreement that innovation is a key determinant for growth of firms, there are few studies that systematically and quantitatively investigate what firms do in their R&D management to create innovation. Utilizing insights from theoretical and empirical studies on innovation, the authors focus on the following four aspects of R&D management: the organizational structure of R&D, staged project management for R&D projects, compensation and incentive schemes for R&D personnel, and a firm’s risk preferences and corporate culture. The authors examine whether and how R&D management practices are linked to the likelihood of firms’ success in making product innovations and the choice between explorative and exploitive innovation. The book furnishes vital information that can be used as a reference for future theoretical and empirical analyses of R&D management practices and innovation. This monograph is highly recommended to academics and practitioners who seek an in-depth and detailed analysis of R&D management.This is an open access book.