- MBA‐IB Difference
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The mathematics are needed for the study of economics and business. The objective of business mathematics is to introduce or review some basic mathematical concepts and methods for students to learn quantitative methods in business, which includes topics such as functions and graphs, matrix algebra, probability and statistics, and differentiation. The topics will be taught by different instructors from the corresponding fields.
Data analysis is an indispensable tool for empirical analysis and data-oriented decision making in the fields of natural science, humanities, and social sciences. This class introduces basic concepts of descriptive statistical methods, linear regression for prediction and its residual analysis with statistical software R through a series of the group works on financial data analyses of all the listed companies in Japan.
This course covers fundamentals on quantitative analysis, including a design of data collection, data analysis strategy, and summarization of the quantitative results. Some exercises are included to apply the statistical tools, such as design of experiments, regression analysis and so forth.
This class is designed to enhance understanding of key techniques of Data Mining which are applied in various fields such as marketing research, medical information analysis etc. Another aim is to acquaint students with basic mathematical descriptions in order to enhance the understanding of professional articles.
This course surveys the importance of information security in the business world by covering its introductory concepts. It helps students understand the principles that frame and define information security and how to implement such practices in the corporate environment. Classes will be a mixture of lectures, discussions, and case studies.
This course provides basic topics regarding quantitative methods, which include probability, probability distributions and descriptive statistics, sampling and estimation, hypothesis testing and so on. Students will learn how to summarize data and how to make appropriate decisions based on data.
This course presents a survey of information system topics from the managerial viewpoint. We will focus on understanding the power of information systems leads with strategic thinking before diving into technical topics. We will go through emergent concepts, including data analytics, security, social media, the sharing economy, disruptive innovation, network effects, etc. Classes will be a mixture of lectures, discussions, and case studies.
Operations management is primarily involved with activities of developing, producing and delivering goods and services. It applies the underlying methodologies of management science to deal with the operations. The focus is on how to combine concepts, models, and methods to help managers develop better systems and make better decisions concerning operations. This course covers five operations management and management science topics, which are PERT/CPM, Linear Programming, Analytic Hierarchy Process, Decision Analysis and Inventory Management Models. The fundamental concepts, models and principles associated with each topic and their applications in operations will be taught by different instructors from the corresponding fields.
Decision analysis provides powerful tools for dealing with complex decisions that involve multiple objectives and/or uncertainty. In this course, we will learn a useful decision process to identify and overcome the challenges of decision making. We will introduce some fundamental concepts, models and methods for decision analysis in various situations such as decision with multiple objectives, decisions under uncertainty and decisions with different decision makers and different/conflict decision objectives, namely game problems. We will make practices to solve some real-world decision problems through group works.
Risk analysis is defined as a systematic process to describe risk, i.e. to present an informative risk picture. Risk analysis is incorporated primarily in risk management and risk-based decision making. The objective of this course is to learn the fundamental concepts of risk analysis and a variety of models and methods to deal with risk identification, risk assessment and risk management problems. A risk filtering, ranking and management (RFRM) process will be introduced and applied to solve some practical risk management problems through group works.
In order to accomplish a project successfully, it is important to carry out systematized management processes, such as requirements definition, planning, executing tasks, and monitoring and control. This course provides the fundamental knowledge of project management. For instance, WBS(Work Breakdown Structure), Scheduling techniques, EVM(Earned Value Management), Cost Estimation and Contract, Risk Management, Quality Assurance and so on.
Understanding behaviors of social systems is one of key factors for success on business and our life. Diagraming techniques, for example, Flow chart, ER Diagram (Entity Relationship Diagram), State chart and UML (Unified Modeling Language) are useful to visualize/design our social systems. Additionally, natural languages, for example, Japanese, English, Spanish and other languages are useful when we will design social models. In this class we will learn text analysis, diagraming techniques, and systems design.
The course begins with the basic concepts and methods of management science that rely on statistical analysis techniques and the art of decision-making under circumstances of constrained optimization. It introduces statistical ideas as they apply to managers. It also covers the fundamental concepts and tools needed to understand the emerging role of business analytics in organizations. It discusses applying business analytics tools in spreadsheets and online environments, how to use and interpret analytic models effectively, and results for making better business decisions.