Excel-Data-Analysis-Modeling-and-Simulation-2nd-Edition-by-Hector

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Excel Data Analysis Modeling and Simulation 2nd Edition by Hector Guerrero

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Author of Excel Data Analysis Modeling and Simulation

Hector Guerrero may be a Professor Emeritus at Mason School of Business at the school of William and Mary, in Williamsburg, Virginia.

He teaches within the areas of business analytics, deciding , statistics, operations, and business quantitative methods.

He has previously taught at the Amos Tuck School of Business at Dartmouth College and therefore the College of Business of the University of Notre Dame.

He is documented among his students for his quest to bring clarity to complex decision problems.

He earned a Ph.D. in Operations and analysis at the University of Washington and a BS in EE and an MBA at the University of Texas.

He has published scholarly add the areas of operations management, product design, and catastrophic planning.

Prior to entering academe, he worked as an engineer for Dow Chemical Company and Lockheed Missiles and Space Co.

He is also very active in consulting and executive education with a good sort of clients––U.S.

Government, international firms, also as many small and enormous U.S. manufacturing and repair firms.

It is commonplace to seek out him relaxing on a quiet beach with a challenging Excel workbook and a superb cabernet.

Excel Data Analysis Modeling and Simulation Contents

  • Introduction to Spreadsheet Modeling
  • Presentation of Quantitative Data: Data Visualization
  • Analysis of Quantitative Data
  • Presentation of Qualitative Data—Data Visualization
  • Analysis of Qualitative Data
  • Inferential Statistical Analysis of knowledge
  • Modeling and Simulation: Part 1
  • Modeling and Simulation: Part 2

Preface to Excel Data Analysis Modeling and Simulation

Why Does the planet Need—Excel Data Analysis, Modeling, and Simulation?

When spreadsheets first became widely available within the early 1980s, it spawned a revolution in teaching.

What previously could only be through with arcane software and large-scale computing was now available to the commoner , on a desktop.

Also, before spreadsheets, most substantial analytical work was done outside the classroom where the tools were; spreadsheets and private computers moved the work into the classroom.

Not only did it change how the info analysis curriculum was taught, but it also empowered students to venture out on their own to explore new ways to use the tools.

I can’t tell you ways many phone calls, office visits, and/or emails I even have received in my teaching career from ecstatic students crowing about what they need just through with a spreadsheet model.

I have been teaching courses associated with business and data analytics and modeling for over 40 years, and that i have watched and took part within the spreadsheet revolution.

During that point , I even have been a witness to the subsequent important observations:

Each successive year has led to more and more demand for Excel-based analysis and modeling skills, both from students, practitioners, and recruiters.
Excel has evolved as an ever more powerful suite of tools, functions, and capabilities, including the recent iteration and basis for this book—Excel 2013.
The ingenuity of Excel users to make applications and tools to affect complex problems continues to amaze me.
Those students who preceded the spreadsheet revolution often find themselves at a loss on where to travel for an introduction to what’s commonly taught to most undergraduates in business and sciences.
Each one of those observations has motivated me to write down this book.

The first suggests that there’s no foreseeable end to the demand for the talents that Excel enables; actually , the necessity for continuing productivity altogether economies guarantees that a private with proficiency in spreadsheet analysis are going to be highly prized by a corporation .

At a minimum, these skills permit you freedom from specialists which will delay or hold you captive while expecting an answer .

This was common within the youth of data technology (IT); you requested that the IT group provide you with an answer or tool and you waited, and waited, and waited.

Today if you would like an answer you’ll roll in the hay yourself. the mixture of the second and third observations suggests that once you couple bright and energetic people with powerful tools and an honest learning environment, wonderful things can happen.

I have seen this throughout my teaching career, also as in my consulting practice. The trick is to supply a teaching vehicle that creates the analysis accessible.

My hope is that this book is such a teaching vehicle. i think that there are three simple factors that facilitate learning—select examples that contain interesting questions, methodically lead students through the rationale of the analysis, and thoroughly explain the Excel tools to realize the analysis.

The last observation has fueled my desire to lend a hand to the various students who skilled the tutorial system before the spreadsheet analysis revolution: to supply them with a book that points them within the right direction.

Several years ago, I encountered a former MBA student during a Cincinnati Airport bookstore. He explained to me that he was trying to find an honest Excel-based book on data analysis and modeling—“You know it’s been quite 20 years since i used to be during a Tuck School classroom, and that i desperately got to understand what my interns seem to be ready to do so easily.”

By providing a broad sort of exemplary problems, from graphical/ statistical analysis to modeling/simulation to optimization, and therefore the Excel tools to accomplish these analyses, most readers should be ready to achieve success in their self-study attempts to master spreadsheet analysis.

Besides an honest compass, students also got to be made conscious of the possible. it’s not usual to listen to from students “Can you employ Excel to try to to this?” or “I didn’t know you’ll do this with Excel!”

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