What you’ll find inside
Business Analytics: Methods, Models, and Decisions, Second Edition by James R. Evans introduces business analytics through the methods used to describe data, make predictions, and select among alternatives. The chapters progress from basic concepts into descriptive, predictive and prescriptive approaches. The supplied file is listed as PDF; check the exact title and edition against your course requirements.
Build foundations in data analysis
The opening chapters define business analytics, discuss data and models, and introduce spreadsheet use. Descriptive analytics then covers visualizing and exploring data, statistical measures, probability distributions, sampling, and inference. These foundations give readers tools for summarizing information, evaluating variation, and understanding the assumptions behind a model before using its results in a decision. Exercises and examples reinforce how to explain analytical results and relate them to an organizational choice.
Develop predictive and prescriptive models
The text progresses to regression, forecasting, data mining, and spreadsheet-based modeling. Simulation and risk analysis extend this work to situations with uncertainty. Later chapters introduce linear and integer optimization, applications of optimization, and decision analysis. The sequence lets students compare questions that describe what has happened, estimate what may happen next, and identify a course of action under stated constraints.
Review the edition and digital file
The second-edition contents refer to supplementary online chapters on nonlinear optimization and optimization under uncertainty. Access to these online materials is included only if specifically stated in the product details. Four sample images are available to inspect selected pages. Verify the edition and confirm PDF compatibility before choosing the file.
Explore related business and economics ebooks or browse the ebook catalog.
ISBN and edition details
ISBN for this edition (reference): 9780321997821
This identifier belongs to a published version of the matching title/edition. A format-specific ISBN for the supplied PDF has not been independently confirmed.
Sunny –
very good ebook for the cost it is being sold in India, excellent content, detailed examples on predictive, prescriptive, Non linear problems. you will get lot of enthu/interest to read the ebook
William –
Lots of typos
Dr. Franco Arda –
I wish I had had this ebook for my MBA
The ebook is easy to read, interesting theory with many practical case studies. Additionally, they go deep into Excel. Great ebook!
DSexton –
This was assigned for a graduate data analytics course. It was easy to follow, well written and easily referenced.
jumul –
good
Rebecca Roth –
First 14 pages of ebook covered over half of the content that was covered in another school’s online course. Totally worth every penny!
King of the Stream –
My fiancé got this for her courses at college. I can’t really review this on her behalf, because I didn’t read/use this ebook. But hey, she passed her course so this must work!
Franco Arda –
I got this ebook as a refresher for business analytics. Normally, I don’t bother with Excel. I use Python to do data science / machine learning. But I wanted to have a quick refresher. If you work too long with a hammer …. I wish I had had this ebook during my MBA. The ebook is easy to read, interesting theory with many practical case studies. Additionally, they go deep into Excel (through an add on). They cover exciting stuff such as: – Stochastic processes – Monte Carlo Simulation – Simple Machine Learning Algoriths – Linear Programming / Optimization Every number cruncher should be excited about those topics 🙂 I certainly see cases where I would use Excel (with an add on), in particular for quick and dirty linear optimization. As a scientific Python user, I always envy Excel’s ability to create visuals in seconds. For us, visuals are a nightmare. Would I use Excel for data science / machine learning? NEVER! Not even to learn it. In Excel, I can’t “read code” ….I’d be totally lost. Great ebook! Read more