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Predictive Analytics: Microsoft Excel Kindle Edition

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Length: 304 pages Word Wise: Enabled Enhanced Typesetting: Enabled
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Editorial Reviews

About the Author

Counting conservatively, this is Conrad Carlberg’s eleventh book about quantitative analysis using Microsoft Excel, which he still regards with a mix of awe and exasperation. A look back at the “About the Author” paragraph in Carlberg’s first book, published in 1995, shows that the only word that remains accurate is “He.” Scary.


Product Details

  • File Size: 48026 KB
  • Print Length: 304 pages
  • Simultaneous Device Usage: Up to 5 simultaneous devices, per publisher limits
  • Publisher: Que Publishing; 1 edition (July 2, 2012)
  • Publication Date: July 2, 2012
  • Sold by: Amazon Digital Services, Inc.
  • Language: English
  • ASIN: B008JWQ8CA
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Enabled
  • Lending: Not Enabled
  • Enhanced Typesetting: Enabled
  • Amazon Best Sellers Rank: #205,838 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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More About the Author

Conrad Carlberg (www.conradcarlberg.com) is a nationally recognized expert on quantitative analysis, and on data analysis and management applications such as Microsoft Excel, SAS and Oracle. He holds a Ph.D. in statistics from the University of Colorado and is a many-time recipient of Microsoft's Excel MVP designation.

Carlberg is a Southern California native. After college he moved to Colorado, where he worked for a succession of startups and attended graduate school. He spent two years in the Middle East, teaching computer science and dodging surly camels. After finishing graduate school, Carlberg worked at US West (a Baby Bell) in product management and at Motorola.

In 1995 he started a small consulting business which provides design and analysis services to companies that want to guide their business decisions by means of quantitative analysis - approaches that today we group under the term "analytics." He enjoys writing about those techniques and, in particular, how to carry them out using the world's most popular numeric analysis application, Microsoft Excel.

Carlberg and his wife live near San Diego with their two cats.

Customer Reviews

Most Helpful Customer Reviews

20 of 21 people found the following review helpful By Adam W Phoenix on September 25, 2012
Format: Paperback
I thought the author did a great job presenting real world examples and techniques. It was nice to seethis much detail while highlighting some of the more advanced options in Excel. Both average and advanced Excel users will appreciate and learn something new in this book. I found the level of detail in the explanation of the statistical calculations appropriate for the assumed audience. This is not an intro to statistics book and I think more users with more experience and a statistical background will appreciate being able to jump right into the core intent of the book and how to leverage Excel as the primary tool.
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13 of 13 people found the following review helpful By Joseph Johnson on February 25, 2013
Format: Paperback Verified Purchase
As an inexperienced Demand Analyst I scrambled to understand the academic literature on forecasting. I was pretty swamped and did not know where to start until I found this book. Carlberg has a way of explaining very complex issues in a way that a beginner can grasp and an intermediate or expert can learn from. His book is funny, intuitive, and really hits home as to where to start when diving into predictive analytics. Although I've read through the book and worked through several of the examples, I keep the book close at hand for a quick reference. Great, great book!
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25 of 29 people found the following review helpful By rrdigitalbookworm on September 18, 2012
Format: Paperback
Excels [use of] Predictive Analytics is a book true to its meaning taking a once complex understanding of powerful statistics equations and applying it through Excel with a meaningful and visual understanding.
Author Conrad Carlberg's book strikes the most effective use of quantitative analysis using forcasting analytics
which to some without statistical analysis background might seem a bit foreign. For those primed and
willing to take the next leap into forcasting predictive analytics, it is a remarkable use of statistics put to its true meaning. The author puts forth an understanding to derive strong probabilities to make powerfully informed business decisions.
For example, Carlberg's book explains a Logistic Regression in a perfected simplistic steps using logical but simple equations. For example he does so by stepping through and analyzing a Purchase/No Purchase preditive analysis(using dicotomous variable) behavior. He concludes his explanation using probability of likelihood stepping through a series of complex formulas (Autocorrelation Formulas(ACFs), Partials(PACFs), Time Series Regression, visually outputting them into barchart and spot graph for analysis and interpretation with all original input calcs handled by Excel. Formulas which took many hours to compute are whittled down to become mere 'program executed tools' of the trade for quick accurate business decision making. There is complete truth to the mathematical elements as he explains it with simplistic meaningful and comprehensible language (again with true examples to follow if you will). A true mathematician at heart. Thank you Mr. Carlberg. You have brought another great myth in 'forecasting statistical analysis' to the forefront and shone light of its true meaning to the masses.
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10 of 12 people found the following review helpful By Gaetan Lion on April 23, 2013
Format: Paperback Verified Purchase
Overall Conrad Carlberg has done an excellent job of covering 9 different quantitative methods related to time series analysis and regression. Carlberg covers methods that are relatively simple such as moving averages and exponential smoothing. He also covers others that are very advanced that few use outside of statisticians such as Principal Component Analysis and Varimax Factor Rotation. But, in all cases he walks the reader slowly and diligently so you get to understand pretty well what those methods are about.

This is a book not only to read, but study (I took 25 pages of notes while reading it over nearly a couple of months), and practice with Excel open and follow his own illustrated examples.

The book also provides some interesting add-ins and support materials available at QUE publishing as indicated within the book. To activate those add-ins, you have to follow the instructions very carefully within the first page of the relevant workbook. I think many reviewers, including myself at first, did not understand how to access the add-ins and thought they did not work or were absent.
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11 of 13 people found the following review helpful By Jeffrey on January 11, 2013
Format: Paperback Verified Purchase
Do yourself a favor and save the $10,000+ on a statistics Master's degree and spend the $35 on this book. Excellent all around. I thought I knew everything about excel until I picked this book up on a whim.
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7 of 9 people found the following review helpful By Sean Findley on October 5, 2012
Format: Paperback Verified Purchase
Most predictive analytics techniques require the use of expensive statistics packages such as SAS, SPSS, etc. Unfortunately, few books use Excel. Conrad, famous Excel God, shows that Excel is indeed a useful tool for this abstract discipline. This book provides a solid 30,000 foot view. All of the basic forecasting models are described. Thankfully, the text is not saturated with mathematical rigor/proofs; rather, an intuitive approach is given. However, a solid knowledge of statistics is a prerequisite otherwise one runs the risk of being buried in jargon. I give the book five stars because you can stampede through it in a night or two if motivated. Visit [...] for how these forecasting techniques can be used for social media.
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2 of 2 people found the following review helpful By Sigma on March 4, 2014
Format: Paperback
Hats off to Mr. Carlberg. Found this book to be just the right amount of theory, example and execution.
Having been a user of PA and stats (though not a 'ician) for years, and owner/user of SPSS, Minitab and others, I always find myself going back to Excel because of the quick ability to personalize the data representation.

My personal experience is that most Excel users won't even care to invest the time to learn PA, so this book is perfect for those who are willing.

Great job, Mr. Carlberg!
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