Today, most business planning routinely begins with a sales forecast. Whether you are an accountant, a marketer, a human resources manager, a data scientist, or a financial analyst, sooner or later, you will have to pred
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Today, most business planning routinely begins with a sales forecast. Whether you are an accountant, a marketer, a human resources manager, a data scientist, or a financial analyst, sooner or later, you will have to predict something. This book is designed to lead students through the most helpful techniques to use in any prediction effort.
New to This Edition•Four new chapters focus on predictive analytics, recognizing the importance of these tools in today's prediction efforts.•Examples of predictive analytics are based on historical data, much like what students may encounter in their own forecasts.•Techniques are explained as procedures, allowing students to replicate them with their own data.•All chapters now include Learning Objectives.•The ForecastX software sections are updated and clarified.Retained Features •Real-world data are used throughout the text, which consists almost entirely of real-world examples, showing readers how to deal with real-life problems and difficulties in a realistic environment.•Extended examples are presented in each chapter. Two examples are used to demonstrate the progression of techniques needed to solve each issue; these examples provide a realistic illustration of the concepts that are relevant to the student used in the text. One example features sales data from The Gap, whereas another example uses domestic car sales data.•By consistently providing all the data in Excel, the leading calculation software used in business, students recognize its compatibility with ForecastX software.•Screenshots of problems help students better conceptualize problems. The edition includes many screenshots of actual problems, and the data for each of these examples and problems are included in the accompanying ForecastX software.
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