This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. The course aim to cover statistical ideas that apply to managers. We will consider two basic themes: first, is recognizing and describing variations present in everything around us, and then modeling and making decisions in the presence of these variations. The fundamental concepts studied in this course will reappear in many other classes and business settings. Our focus will be on interpreting the meaning of the results in a business and managerial setting.
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来自INFERENTIAL AND PREDICTIVE STATISTICS FOR BUSINESS的热门评论
Very good introductory Statistics course. The topic selection is very pertinent to meet the need of a manager to analyze data and to make decision. Quality of teaching is GREAT.
Great course! Incredibly well organized and clear. I was terrified of Stats before I took this class, now I feel confident and am seeing my entire world differently. Thank you!
Very well produced. The modules are clear and easy to follow. Maybe I missed it but it would be good to supply all the related example data in Excel to be able to practice.
The Professor is gracious lady and commands huge respect. Very clear and confident in her knowledge and style of teachings. I wish Ma'am nothing less than the very best.
关于 管理经济学和商业分析 专项课程
In order to effectively manage and operate a business, managers and leaders need to understand the market characteristics and economic environment they operate in. In this Specialization, you will build a solid understanding of the operation of markets and the macro-economic environment with real-world examples. You will be able to identify firm and country-level economic factors that impact business decisions, develop an analytical framework using statistical tools, and apply economic theory and data in the analysis of business environment and trends to make effective business decisions.