The book provides nine tutorials on optimization, machine learning, data mining and forecasting all within the confines of a spreadsheet. Each tutorial uses a real-world problem and the author guides the reader using query's the reader might ask as how to craft a solution using the correct data science technique. Hosting these nine spreadsheets for download will be necessary so that the reader can work the problems along with the book. Table of contents: introduction everything you ever needed to know about spreadsheets but were too afraid to ask cluster analysis part i: using k-means to segment your customer base naïve bayes and the incredible lightness of being an idiot optimization modeling: because that "fresh squeezed" orange juice ain't gonna blend itself cluster analysis part ii: network graphs and community detection the granddaddy of supervised artificial intelligence-regression ensemble models: a whole lot of bad pizza forecasting: breathe easy, you can't win outlier detection: just because they're odd doesn't mean they're unimportant moving from spreadsheets into r conclusion index - from Amzon